
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
Run a fast 2-agent pre-submission check for an economics paper — focuses on contribution, identification, and causal overclaiming. Completes in ~1 minute.
Run a 6-agent pre-submission panel review for a grant proposal targeting a specified funder or program
Document datasets, variables, sources, and merge keys for replication
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc + binscatter. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step Stata pipeline an applied economist runs on every paper — (1) data import & cleaning (use/import, destring, misstable, duplicates, merge assert), (2) variable construction (gen/egen/winsor2/xtile/xtset with L./F./D.), (3) descriptive statistics & Table 1 (tabstat/balancetable/asdoc), (4) classical diagnostic tests (sktest/swilk/hettest/imtest/xtserial/xttest3/vif/dfuller/kpss/hausman/estat overid), (5) baseline modeling (reg/xtreg/reghdfe/ivreg2/ivregress/csdid/did_imputation/eventstudyinteract/sdid/rdrobust/synth/psmatch2/teffects/heckman/qreg/ppmlhdfe), (6) robustness battery (bacondecomp/honestdid/rwolf/ritest/wildbootstrap/oster), (7) further analysis (subgroup/triple-diff/interactions/medsem/marginsplot/binscatter by group), (8) publication-ready tables & figures (esttab/outreg2/estout/coefplot/marginsplot/rdplot/twoway combined). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `teffects ipw` / `teffects ipwra` / `teffects aipw` / `eltmle`, Mendelian randomization via `mrrobust` (IVW / Egger / weighted median) and `mregger` / `mrpresso`, KM / Cox / AFT / RMST survival via `sts` / `stcox` / `streg` / `strmst2`, E-value sensitivity via `evalue` (Linden-Mathur), principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `ddml` / `pdslasso`, S/T/X/R/DR meta-learners via `crforest` and `ddml interactive`, causal forest via `crforest` / `cforest`, BART/BCF via `bart` / `bartCause`-style externals, CATE distribution + policy tree via `crforest`, off-policy evaluation, conformal causal externals, fairness audit, DAG learning via `pcalg` / external Python callouts). Use when the user asks for a complete Stata empirical analysis, wants a reproducible .do-file pipeline, needs a Stata counterpart to the Python StatsPAI / Full-empirical-analysis-skill, or names a specific Stata step in isolation ("run reghdfe with two-way clustering", "csdid event study", "winsor2 at 1%", "esttab to LaTeX", "coefplot with CI", "ivreg2 weak-IV test", "synth_runner placebos", "teffects psmatch balance check"). Mode A triggers on "target trial emulation Stata", "teffects ipw aipw", "eltmle", "mrrobust", "mregger weighted median", "stcox AFT survival", "strmst2", "evalue Stata", "STROBE Stata", "公共健康 Stata", "流行病学 Stata". Mode B triggers on "ddml Stata", "pdslasso", "crforest causal forest Stata", "policy tree Stata", "因果机器学习 Stata".
Plan, draft and refine research papers with reproducible analysis and publication-ready manuscripts.
Integrate AI tools into economic research, teaching, and policy analysis with attention to privacy and reproducibility.
Standardized Python & Stata coding practices for empirical research projects
Use when aer-identification has fixed the design, after methodology choice and before aer-robustness or aer-tables-figures, to run an AER-track analysis with StatsPAI — the agent-native Python engine and MCP server for causal inference, robustness, sensitivity, and publication-ready table export.
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
Use when selecting, implementing, or stress-testing the causal identification strategy for an empirical economics manuscript — difference-in-differences (including staggered designs), instrumental variables (including weak-IV-robust inference), regression discontinuity, synthetic control, or shift-share / Bartik. Apply before writing the introduction or results.
Create concise policy briefs that translate research into actionable recommendations for policymakers and stakeholders.
Use when running the final pre-submission audit for an AER, AER:Insights, or AEJ manuscript — length, format, cover letter, per-author disclosure statements, file packaging, and routing among the AEA journal family. Apply immediately before clicking submit.
Use when responding to a Revise & Resubmit decision from AER, AER:Insights, or an AEJ, and a point-by-point response letter plus aligned manuscript revisions are needed. Handles triage, the concede / clarify / push-back decision, and the response-letter format that editors actually read.
Run a 6-agent pre-submission review of a pre-analysis plan (PAP) for a specified registration target or journal
Use when a complete draft exists and needs an adversarial internal review before submission — simulating the AER desk screen and three referee reports with calibrated severity, scoring the paper against the editorial rubric, and producing a prioritized revise list. Apply after aer-consistency passes and before aer-submission; rerun until the simulated verdict is at least major R&R.
Coordinate writing, revision, and submission workflows for collaborative academic and policy documents.
Structure responses to referee reports for R&R submissions
Project directory organization and script naming conventions for research
Summarize academic papers, extract key findings, and identify research gaps
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.
Use when the main empirical results exist but the manuscript lacks the robustness, heterogeneity, mechanism, and placebo checks that AER referees will demand. Apply after aer-identification and before aer-introduction so that the value-added paragraph can reference these tests.
Use when positioning a manuscript against the existing economics literature, building the antecedents map for the introduction, deciding what to cite, or verifying that every reference in the bibliography is real, correctly attributed, and cited to the published version. Apply at topic selection for the novelty scan and again before drafting the introduction.
Review research code for reproducibility and quality, extract the paper's main empirical claims, compare paper to code, and write a constructive markdown report. Designed for social science / economics projects with LaTeX papers and Stata, R, or Python code.
Use when deciding which AER-skills sub-skill to use next, before choosing a specialized skill or after a user asks how to sequence manuscript work from topic selection through rebuttal for AER, AER:Insights, or AEJ journals. Routes — does not replace — the specialized skills.
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery) — OR in distributional / gap-decomposition style (Oaxaca–Blinder `sp.oaxaca`, Kitagawa `sp.kitagawa_decompose`, DiNardo–Fortin–Lemieux `sp.dfl_decompose`, Gelbach `sp.gelbach`, Fairlie `sp.fairlie`, RIF / FFL `sp.rif_decomposition`, all reachable through the `sp.decompose` dispatcher). Also covers exporting multi-column regression tables to Word / Excel / LaTeX (Stata outreg2 / esttab / R modelsummary equivalent) and bundling an entire replication appendix into one .docx / .xlsx / .tex file. Triggers on keywords "StatsPAI", "statspai", "AER empirical analysis", "applied micro pipeline", "Table 1 balance", "event study", "first-stage F", "Oster bound", "honest_did", "spec_curve", "callaway_santanna", "dragonnet", "text as treatment", "outreg2 in Python", "regression table to Word/Excel", "sp.regtable", "sp.collect", "sp.paper_tables", "sp.feols", "summary_col", "modelsummary", "AER style table", "QJE style table", "epidemiology pipeline", "target trial emulation", "g-formula", "IPTW", "TMLE", "Mendelian randomization", "STROBE", "TRIPOD", "公共健康", "流行病学", "DML", "double machine learning", "causal forest", "meta-learner", "CATE", "conformal causal", "policy learning", "因果机器学习", "ML causal", "decomposition", "Oaxaca-Blinder", "Kitagawa", "DiNardo-Fortin-Lemieux", "DFL", "Gelbach", "RIF decomposition", "wage gap decomposition", "sp.decompose", "sp.oaxaca".
Strategic research leadership for designing high-impact research agendas, coordinating teams, and translating research into policy and institutional influence.
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step pipeline an applied economist or quantitative social scientist runs on every paper — (1) data cleaning, (2) variable construction & transformation, (3) descriptive statistics & Table 1, (4) statistical diagnostic tests, (5) baseline empirical modeling, (6) robustness battery, (7) further analysis (mechanism, heterogeneity, mediation, moderation), (8) publication-ready tables & figures. **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation via `zepid` / hand-rolled `pandas`, IPTW + g-formula + TMLE doubly-robust triplet via `zepid` / `econml` / `lifelines`, Mendelian randomization via `pymr` / `mrtool` (or `rpy2` → `MendelianRandomization`/`TwoSampleMR`), KM / AFT / Cox survival via `lifelines`, E-value sensitivity, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `econml.dml` / `doubleml`, S/T/X/R/DR meta-learners via `econml.metalearners` / `causalml`, causal forest via `econml.grf` / `causalml`, Dragonnet / TARNet / CEVAE neural causal via `causalml`, BCF via `pymc-bart` / `bcf-py`, matrix completion, CATE distribution + policy tree via `econml.policy` / `policytree-py`, off-policy evaluation, conformal causal via `mapie`, fairness audit via `fairlearn`, DAG learning via `causal-learn` / `cdt` / LLM-assisted). Prescribes which library to reach for at each step, shows the canonical code, and links to deeper `references/` files for variant-specific patterns. Use when the user asks for a **complete empirical analysis** in Python, wants to replicate an applied-economics paper from scratch, needs a reproducible workflow that is NOT opinionated on any single vertical package (contrast with StatsPAI), wants explicit control over every estimator and diagnostic, or asks "how do I write a full empirical pipeline in Python?". Also triggers when the user names a specific classical step in isolation — "winsorize at 1/99%", "run Breusch-Pagan", "build a Table 1 balance table", "do a placebo test", "event study plot", "mediation analysis" — and wants it wired into the broader pipeline. Mode A triggers on "target trial emulation", "IPTW", "TMLE", "Mendelian randomization", "STROBE", "公共健康", "流行病学". Mode B triggers on "DML", "double machine learning", "causal forest", "meta-learner", "Dragonnet", "BCF", "policy tree", "conformal causal", "fairness audit", "因果机器学习".
Use when assembling the AEA Data and Code Availability deposit for an AER, AER:Insights, or AEJ acceptance, writing the README, or auditing a replication package before the AEA Data Editor review. Implements the current AEA policy, including the February 2026 Data and Code Availability Policy.
Use when evaluating whether a research idea clears the AER top-5 bar, when routing between AER, AER:Insights, and the AEJ family, or when sharpening a fuzzy contribution sentence into one publishable claim. Apply before any writing begins.
Use when constructing or revising regression tables, descriptive statistics tables, or figures after results are estimated and before submission for an AER, AER:Insights, or AEJ manuscript. Implements AER booktabs house style, regression-table layout, and figure-note conventions.
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid + MatchIt + WeightIt + cobalt + ebal + grf + DoubleML + mediation + marginaleffects + modelsummary + kableExtra + gt + ggplot2 + ggpubr + cowplot + binsreg. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step R pipeline an applied economist runs on every paper — (1) data import & cleaning (read_dta/read_csv, naniar, janitor, validate-merges), (2) variable construction (mutate/across/winsorize/group_by + lag/lead with dplyr), (3) descriptive statistics & Table 1 (gtsummary, modelsummary::datasummary, tableone), (4) classical diagnostic tests (shapiro/jarque.bera.test/bptest/dwtest/bgtest/vif/adf.test/kpss.test/Hausman), (5) baseline modeling (fixest::feols, ivreg, did::att_gt, eventstudyr, sun_ab, did_imputation, synthdid, rdrobust, MatchIt, WeightIt, grf::causal_forest, DoubleML, mediation), (6) robustness battery (modelsummary stack, clubSandwich CRSE, fwildclusterboot, ri2, robomit Oster, bacondecomp, HonestDiD), (7) further analysis (interactions + marginaleffects, mediation::mediate, gsem via lavaan, dose-response splines, grf CATE), (8) publication-ready tables & figures (modelsummary, kableExtra, gt, stargazer, texreg, flextable to LaTeX/Word/HTML; ggplot2 + ggpubr + cowplot + binsreg + iplot for figures). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `WeightIt` / `gfoRmula` / `tmle` / `ltmle`, Mendelian randomization via `MendelianRandomization` / `TwoSampleMR` / `MRPRESSO`, KM / Cox / AFT / RMST survival via `survival` / `survminer` / `flexsurv`, E-value sensitivity via `EValue`, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `DoubleML`, S/T/X/R/DR meta-learners via `causalweight` / `grf`, causal forest via `grf::causal_forest`, BART/BCF via `bartCause` / `bcf`, matrix completion via `MCPanel`, CATE distribution + policy tree via `policytree`, off-policy evaluation, conformal causal via `conformalInference` / `cfcausal`, fairness audit via `fairmodels`, DAG learning via `pcalg` / `bnlearn` / LLM-assisted). Use when the user asks for a complete R empirical analysis, wants a tidyverse-style reproducible R script / Quarto workflow, prefers fixest over reghdfe, needs the R counterpart to StatsPAI / 00.1 / 00.2, or names a specific R step in isolation ("feols with cluster", "MatchIt nearest neighbor", "bacondecomp in R", "gtsummary table 1", "modelsummary to Word"). Mode A triggers on "target trial emulation R", "tmle ltmle", "MendelianRandomization", "TwoSampleMR", "MRPRESSO", "survival cox AFT", "STROBE R", "EValue R", "公共健康 R", "流行病学 R". Mode B triggers on "DoubleML R", "grf causal forest", "policytree", "bartCause bcf", "conformal causal R", "fairmodels", "pcalg NOTEARS", "因果机器学习 R".
Checklist of empirical robustness tests for finance/economics papers
Run a 6-agent pre-submission referee report for an academic paper targeting a specified journal
Use when drafting or rewriting the introduction of an economics manuscript targeted at AER, AER:Insights, or an AEJ, or when compressing an abstract to the mandatory 100-word limit. Implements the Keith Head / Bellemare five-paragraph formula and AER-specific formatting conventions. Apply after the body sections exist.
Use when auditing a finished or near-finished AER, AER:Insights, or AEJ manuscript for internal consistency: headline numbers across abstract, introduction, results, and tables; sample sizes; log-point and percentage-point conversions; cross-references; and in-text-citation/bibliography matching. Apply after the body and exhibits exist, before aer-referee-sim and aer-submission.
Use when drafting or revising the body sections of an AER, AER:Insights, or AEJ manuscript — institutional background, data, empirical strategy, results, mechanisms, and conclusion. Covers equation conventions, results-paragraph narration, magnitude interpretation, and back-of-envelope policy calculations. Apply after the empirics are stable and before or alongside aer-introduction.
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
Generate a conference poster (article + tcbposter LaTeX → A0/A1 PDF + editable PPTX + SVG) from a compiled paper. Use when user says "做海报", "制作海报", "conference poster", "make poster", "生成poster", "poster session", or wants to create a poster for a conference presentation.
Autonomous multi-round research review loop. Repeatedly reviews via Codex MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
Verify references in an academic paper: check whether each BibTeX entry is real, whether in-text citations match the cited paper's actual content, and produce a structured verification report. Use when user says "验证参考文献", "ref verify", "check references", "核实引用", "引用是否正确", or wants to audit citations in a LaTeX manuscript.
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
Proofread and verify academic papers in LaTeX. Runs 19 sequential checks covering titles, consistency, citations, formatting, theoretical tension in motivation, concise results reporting, cross-section repetition, em-dash usage, and auxiliary-text-to-footnote conversion. Trigger when user says "check paper" / "proofread" / "paper-checker" / "校对" / "核查论文".
Evaluate a paper's contribution novelty, identify best-fit SSCI journal fields and ABS star rating, and recommend 20 target journals. Trigger when user says "paper submission" / "paper-submission" / "投稿评估" / "期刊推荐" / "target journal" / "选刊".
Generate academic referee reports for economics/finance papers, followed by a 150-word letter to the editor with recommendation (Reject / Major Revision) and Kai Wu signature. Two modes (normal / high-level), configurable number of comments; recommendation choice drives evaluation tone (Reject → negative, Major Revision → neutral). Trigger when user says "referee report" / "write referee report" / "审稿报告" / "写审稿意见" / "generate referee report" / "review this paper".
Revise an academic paper based on journal referee reports. Reads referee comments from review report or annotated manuscript, then directly modifies main.tex one comment at a time with user approval. Generates response letter after revision. Trigger when user says "referee revise" / "paper-referee-revise" / "审稿意见修改" / "根据审稿人意见修改" / "referee report".
Generate master's thesis review reports (硕士论文评阅意见) calibrated to a given score. Outputs academic evaluation and shortcomings/suggestions in Chinese. Trigger when user says "master thesis review" / "硕士论文评阅" / "论文评阅" / "评阅意见" / "thesis review".
This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
Deploy and run ML experiments on local or remote GPU servers. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.
Rent, manage, and destroy GPU instances on vast.ai. Use when user says "rent gpu", "vast.ai", "rent a server", "cloud gpu", or needs on-demand GPU without owning hardware.
Generate conference presentation slides (beamer LaTeX → PDF + editable PPTX) from a compiled paper, with speaker notes and full talk script. Use when user says "做PPT", "做幻灯片", "make slides", "conference talk", "presentation slides", "生成slides", "写演讲稿", or wants beamer slides for a conference talk.
Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.
Autonomously improve a generated paper via GPT-5.4 xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.
Correct grammar errors, typos, and improve academic readability in LaTeX, Markdown, or plain-text manuscripts. Scans the document once, then walks through every issue one-by-one asking for approval before applying each fix. Trigger when the user says "readability", "check grammar", "fix typos", "proofread for grammar", "improve readability", "polish wording", "语言润色", "修语法", or asks you to clean up the prose in a paper/chapter/section without wanting full content restructuring.
Generate publication-quality AI illustrations for academic papers using Gemini image generation. Creates architecture diagrams, method illustrations with Claude-supervised iterative refinement loop. Use when user says "生成图表", "画架构图", "AI绘图", "paper illustration", "generate diagram", or needs visual figures for papers.
Get a deep critical review of research from GPT via Codex MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
Use when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.
Draft LaTeX paper section by section from an outline. Use when user says "写论文", "write paper", "draft LaTeX", "开始写", or wants to generate LaTeX content from a paper plan.
Full research pipeline: Workflow 1 (idea discovery) → implementation → Workflow 2 (auto review loop). Goes from a broad research direction all the way to a submission-ready paper. Use when user says "全流程", "full pipeline", "从找idea到投稿", "end-to-end research", or wants the complete autonomous research lifecycle.
Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says "找idea全流程", "idea discovery pipeline", "从零开始找方向", or wants the complete idea exploration workflow.
Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says "DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning.
Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.
Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.
Generate Mermaid diagrams from user requirements. Saves .mmd and .md files to figures/ directory with syntax verification. Supports flowcharts, sequence diagrams, class diagrams, ER diagrams, Gantt charts, and 18 more diagram types.
公司金融实证研究的"漏斗式选题查找器"。互动开场先后询问 (1) 研究方向、(2) 候选标题数量 N, 再扫描全球文献(已出版英文学术期刊 + SSRN working paper + 全球高校 department seminar 1 年内日程),基于 Edmans (2024) "1000 Rejections" 红线生成 N 个候选标题,**通过并行 subagent(Agent 工具)批量生成计划书 + 查新;每个 subagent 必须强制调用 Skill 工具加载 econfin-proposal 与 novelty-check 两个预设 skill 完成各自模块**,**只有当 novelty score >= 9 时(即 JF/JFE/RFS 顶刊层次),subagent 才把 proposal + 查新报告合并的 md 写入 F:\Dropbox\CC\选题大全\<研究方向短名>\(以"简短选题名称-分数"命名,子文件夹名由 Step 0 从用户输入的研究方向派生);< 9 分的选题在 subagent 内部直接丢弃,绝不写盘、绝不输出**。当用户说"找选题"、"帮我找选题"、"想做 X 方向"、 "empirical CF idea search"、"批量生成研究计划书"、"100 ideas"、"econfin-idea-finder" 时触发。
This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
Strategic research companion — brainstorm, evaluate, and decide on research directions. TRIGGER when the user wants to brainstorm research, evaluate research ideas, do project triage, or explore a problem space. Orchestrates brainstormer, idea-critic, and research-strategist agents through a 6-phase pipeline: Seed → Diverge → Evaluate → Deepen → Frame → Decide. Includes Carlini's conclusion-first test.
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission. Codex designs ablations from a reviewer's perspective, CC reviews feasibility and implements.
This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
Scaffold a new research project with standard directory structure, CLAUDE.md template, and documented README. Use this at the start of every new project to ensure consistent organization.
Download, split, and deeply read academic PDFs. Use when asked to read, review, or summarize an academic paper. Splits PDFs into 4-page chunks, reads them in small batches, and produces structured reading notes — avoiding context window crashes and shallow comprehension.
Monitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.
Generate a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.
Automatically write empirical sections of academic papers in LaTeX by reading tables/figures from a PDF. Trigger when user wants to write a paper from empirical results, has tables/figures in PDF, or says "write paper" / "paper-writer" / "写论文".
Generate publication-quality figures and tables from experiment results. Use when user says "画图", "作图", "generate figures", "paper figures", or needs plots for a paper.
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
Revise an academic paper based on internal review comments. Reads review report or annotated manuscript, then applies revisions one by one with user approval. Trigger when user says "self revise" / "paper-selfrevise" / "内部修改" / "根据审稿意见修改".
Compile LaTeX paper to PDF, fix errors, and verify output. Use when user says "编译论文", "compile paper", "build PDF", "生成PDF", or wants to compile LaTeX into a submission-ready PDF.
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
Structures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.
Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says "robotics idea discovery", "机器人找idea", "embodied AI idea", "机器人方向探索", "sim2real 选题", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.
Create and compile beautiful Beamer presentations following the Rhetoric of Decks philosophy. Use when making slides, creating decks, or compiling .tex presentation files.
Generate a conference poster (article + tcbposter LaTeX → A0/A1 PDF + editable PPTX + SVG) from a compiled paper. Use when user says "做海报", "制作海报", "conference poster", "make poster", "生成poster", "poster session", or wants to create a poster for a conference presentation.
Generate pixel art SVG illustrations for READMEs, docs, or slides. Use when user says "画像素图", "pixel art", "make an SVG illustration", "README hero image", or wants a cute visual.
Writes rigorous mathematical proofs for ML/AI theory. Use when asked to prove a theorem, lemma, proposition, or corollary, fill in missing proof steps, formalize a proof sketch, 补全证明, 写证明, 证明某个命题, or determine whether a claimed proof can actually be completed under the stated assumptions.
Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.
Draft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use when user says "write grant", "grant proposal", "申請書", "write KAKENHI", "科研費", "基金申请", "写基金", "NSF proposal", or wants to turn research ideas into a funding application.
Generate a conference poster (article + tcbposter LaTeX → A0/A1 PDF + editable PPTX + SVG) from a compiled paper. Use when user says "做海报", "制作海报", "conference poster", "make poster", "生成poster", "poster session", or wants to create a poster for a conference presentation.
Generate conference presentation slides (beamer LaTeX → PDF + editable PPTX) from a compiled paper, with speaker notes and full talk script. Use when user says "做PPT", "做幻灯片", "make slides", "conference talk", "presentation slides", "生成slides", "写演讲稿", or wants beamer slides for a conference talk.
Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says "rebuttal", "reply to reviewers", "ICML rebuttal", "OpenReview response", or wants to answer external reviews safely.
Generate conference presentation slides (beamer LaTeX → PDF + editable PPTX) from a compiled paper, with speaker notes and full talk script. Use when user says "做PPT", "做幻灯片", "make slides", "conference talk", "presentation slides", "生成slides", "写演讲稿", or wants beamer slides for a conference talk.
Polish English academic papers for SSCI journal submission. This skill checks grammar, improves readability, and enhances academic tone. Use when the user asks to polish, proofread, edit, or improve their English academic paper, manuscript, or article — especially when targeting SSCI, SCI, or other international journals. Also use when the user asks to "润色", "修改语法", "提升学术性", "polish my paper", or mentions their paper needs language improvement for journal submission. Always trigger on any request involving academic English polishing, even if the user doesn't explicitly say "SSCI."
专业Marp演示文稿制作助手。支持完整工作流程:工作空间初始化、内容分析、slides制作、多维度审阅、中文语言规范审阅(中文演示文稿)、PNG转换检查、终稿确定。所有产出物集中管理在项目工作文件夹中。当用户提到"制作slides"、"做PPT"、"演示文稿"、"Marp"、"幻灯片"、"presentation"等关键词时自动启用。Professional Marp presentation assistant with complete workflow: workspace initialization, content analysis, slide creation, multi-dimensional review, Chinese language review (for Chinese presentations), PNG conversion check, and finalization. All outputs organized in project workspace.
Systematic peer review toolkit. Evaluate methodology, statistics, design, reproducibility, ethics, figure integrity, reporting standards, for manuscript and grant review across disciplines.
Generate professional slide deck images from academic papers and content. Creates comprehensive outlines with style instructions, auto-detects figures from PDFs, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", or "slide deck" for papers.
Write competitive research proposals for NSF, NIH, DOE, and DARPA. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints. Output: optimized detailed outline ready for systematic writing (use with academic-paper-composer skill).
Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for "review paper", "survey", "literature review", "综述", "systematic review", or mentions of writing academic reviews on deep learning for medical imaging.
Generate academic research proposals for PhD applications. Use when user asks to "write a research proposal", "create PhD proposal", "generate research plan", "撰写研究计划", "写博士申请", "doctoral proposal", or mentions specific research topics for PhD application. Supports STEM, humanities, and social sciences with field-specific adaptations. Follows Nature Reviews-style academic writing conventions. Supports both English and Chinese output based on user preference.
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.
专业Marp演示文稿制作助手。支持完整工作流程:工作空间初始化、内容分析、slides制作、多维度审阅、中文语言规范审阅(中文演示文稿)、PNG转换检查、终稿确定。所有产出物集中管理在项目工作文件夹中。当用户提到"制作slides"、"做PPT"、"演示文稿"、"Marp"、"幻灯片"、"presentation"等关键词时自动启用。Professional Marp presentation assistant with complete workflow: workspace initialization, content analysis, slide creation, multi-dimensional review, Chinese language review (for Chinese presentations), PNG conversion check, and finalization. All outputs organized in project workspace.
Restructure an academic paper's title and section structure to match a target journal's house style. Asks the user to specify the target journal first, then adjusts main.tex accordingly (title wording and case, section skeleton, heading case, numbering scheme, merging/splitting sections). Trigger when user says "paper style" / "paper-style" / "期刊风格" / "按目标期刊调整" / "调整为XX风格" / "JFE风格" / "convert to journal style" / "restructure for [journal]", or wants a paper's title/sections reformatted for a specific journal submission.
Orchestrate the complete post-first-draft polishing pipeline for an academic LaTeX paper by invoking five existing skills in fixed order: (1) paper-polish, (2) paper-self-revise, (3) paper-style, (4) paper-polish again, (5) reference-verify. Trigger when user says "paper pipeline" / "paper-pipeline" / "论文流水线" / "全流程打磨" / "一条龙打磨" / "初稿打磨" / "full polish pipeline" / "run the whole pipeline", or wants the entire post-draft polishing sequence run on a paper folder. Use this skill whenever the user asks for several paper-finishing steps (polish + revise + style + reference check) on one manuscript in one go, even if they don't name every individual skill.
Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inquiry across domains.
Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
Two-stage paper screening - abstract scoring then deep dive for specific data extraction
Use Unpaywall API to find free full-text versions of paywalled papers
Introduction to literature search & review skills - systematic paper finding, screening, extraction, and citation traversal
Collaboratively build and refine paper screening rubrics through brainstorming, test-driven development, and iterative feedback
Use parallel subagents for large-scale paper screening and deep dive analysis
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
End-to-end statistical writing assistant for LaTeX - draft title/abstract/keywords, expand outlines into sections, audit manuscripts, write reviewer reports and response letters, and scaffold book manuscripts.
Check if medicinal chemistry papers are in ChEMBL database to access curated bioactivity data
Smart backward and forward citation following via Semantic Scholar, with relevance filtering and deduplication
PubMed search with keyword optimization, result parsing, and metadata extraction
Safely remove intermediate files from completed research sessions while preserving important data
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
Main orchestration workflow for systematic literature research - search, evaluate, traverse, synthesize
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process: (1) create section outlines with key points using research-lookup, (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.
Apply the ScholarEval framework to systematically evaluate scholarly work across quality dimensions (novelty, rigor, significance, and clarity). Use to critique academic papers, research proposals, literature reviews, or grant applications and produce a structured, criterion-based assessment.
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
Dense, machine-readable API reference for PyFixest — high-dimensional fixed-effects OLS/WLS/IV and Poisson (feols, fepois, feglm), clustered/robust standard errors, R-style formula syntax, and post-estimation. Use when writing or debugging Python fixed-effects regressions with the pyfixest package.
Polish English academic papers for SSCI journal submission. This skill checks grammar, improves readability, and enhances academic tone. Use when the user asks to polish, proofread, edit, or improve their English academic paper, manuscript, or article — especially when targeting SSCI, SCI, or other international journals. Also use when the user asks to "润色", "修改语法", "提升学术性", "polish my paper", or mentions their paper needs language improvement for journal submission. Always trigger on any request involving academic English polishing, even if the user doesn't explicitly say "SSCI."
Perform an exhaustive, multi-pass proofread and copy-edit of an applied-microeconomics manuscript to top-economics-journal standards (AER, QJE, Econometrica, ReStud), checking prose, equations, table notes, footnotes, and citations for avoidable errors. Use before submitting or circulating an empirical economics paper.
Run a full 6-phase autonomous replication of a biomedical/epidemiology paper against UK Biobank or similar cohort data, producing Python and R scripts plus a validated replication report. Use when asked to replicate a paper end-to-end, or when invoked as /replicate-paper [paper.pdf] [data.csv|dta].
调查数据清洗Skill。处理调查数据(CGSS/CHIP/CSS等)时的标准化清洗流程,包括缺失值处理、变量编码统一、数据异常值检测。触发词:数据清洗/调查数据/codebook/数据清洗流程/问卷数据处理
双重差分(DID)实证审查Skill。做DID分析前必须检查平行趋势假设、画图可视化、报告违背情况。触发词:DID审查/双重差分检查/平行趋势/DiD reviewer/difference-in-differences
经济学顶刊标准审稿Skill。按AER/QJE/Econometrica/JPE顶刊标准审查论文输出(图表+回归表),列出潜在致命缺陷。触发词:顶刊审稿/论文审查/econ reviewer/经济学期刊标准/PR
R语言实证分析优化Skill。优化R代码效率、处理大规模面板数据、加速回归计算(并行化、向量化、向量化)。触发词:R语言优化/R加速/R性能优化/大规模数据处理/R optimization
LaTeX回归表格生成Skill。辅助生成符合AER/QJE等顶刊格式的三线表,包括标准误聚类标注、显著性星标、固定效应标注。触发词:LaTeX表格/回归表/三线表/table制作/latex table
学术引用核查Skill。要求每条引用必须定位到PDF原页,区分直接引用/间接引用,找不到原文则标注"待核"。触发词:引用核查/检查引用/citation check/核实文献/引用 fidelity
苏格拉底诘问式研究选题Skill。通过连续追问帮你厘清研究思路、聚焦研究子领域、明确研究问题(RQ),识别出未被研究过的新意选题。触发词:帮我选题/研究问题不清晰/想做一个有新意的论文/不断问我问题/厘清思路
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step pipeline an applied economist or quantitative social scientist runs on every paper — (1) data cleaning, (2) variable construction & transformation, (3) descriptive statistics & Table 1, (4) statistical diagnostic tests, (5) baseline empirical modeling, (6) robustness battery, (7) further analysis (mechanism, heterogeneity, mediation, moderation), (8) publication-ready tables & figures. **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation via `zepid` / hand-rolled `pandas`, IPTW + g-formula + TMLE doubly-robust triplet via `zepid` / `econml` / `lifelines`, Mendelian randomization via `pymr` / `mrtool` (or `rpy2` → `MendelianRandomization`/`TwoSampleMR`), KM / AFT / Cox survival via `lifelines`, E-value sensitivity, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `econml.dml` / `doubleml`, S/T/X/R/DR meta-learners via `econml.metalearners` / `causalml`, causal forest via `econml.grf` / `causalml`, Dragonnet / TARNet / CEVAE neural causal via `causalml`, BCF via `pymc-bart` / `bcf-py`, matrix completion, CATE distribution + policy tree via `econml.policy` / `policytree-py`, off-policy evaluation, conformal causal via `mapie`, fairness audit via `fairlearn`, DAG learning via `causal-learn` / `cdt` / LLM-assisted). Prescribes which library to reach for at each step, shows the canonical code, and links to deeper `references/` files for variant-specific patterns. Use when the user asks for a **complete empirical analysis** in Python, wants to replicate an applied-economics paper from scratch, needs a reproducible workflow that is NOT opinionated on any single vertical package (contrast with StatsPAI), wants explicit control over every estimator and diagnostic, or asks "how do I write a full empirical pipeline in Python?". Also triggers when the user names a specific classical step in isolation — "winsorize at 1/99%", "run Breusch-Pagan", "build a Table 1 balance table", "do a placebo test", "event study plot", "mediation analysis" — and wants it wired into the broader pipeline. Mode A triggers on "target trial emulation", "IPTW", "TMLE", "Mendelian randomization", "STROBE", "公共健康", "流行病学". Mode B triggers on "DML", "double machine learning", "causal forest", "meta-learner", "Dragonnet", "BCF", "policy tree", "conformal causal", "fairness audit", "因果机器学习".
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid + MatchIt + WeightIt + cobalt + ebal + grf + DoubleML + mediation + marginaleffects + modelsummary + kableExtra + gt + ggplot2 + ggpubr + cowplot + binsreg. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step R pipeline an applied economist runs on every paper — (1) data import & cleaning (read_dta/read_csv, naniar, janitor, validate-merges), (2) variable construction (mutate/across/winsorize/group_by + lag/lead with dplyr), (3) descriptive statistics & Table 1 (gtsummary, modelsummary::datasummary, tableone), (4) classical diagnostic tests (shapiro/jarque.bera.test/bptest/dwtest/bgtest/vif/adf.test/kpss.test/Hausman), (5) baseline modeling (fixest::feols, ivreg, did::att_gt, eventstudyr, sun_ab, did_imputation, synthdid, rdrobust, MatchIt, WeightIt, grf::causal_forest, DoubleML, mediation), (6) robustness battery (modelsummary stack, clubSandwich CRSE, fwildclusterboot, ri2, robomit Oster, bacondecomp, HonestDiD), (7) further analysis (interactions + marginaleffects, mediation::mediate, gsem via lavaan, dose-response splines, grf CATE), (8) publication-ready tables & figures (modelsummary, kableExtra, gt, stargazer, texreg, flextable to LaTeX/Word/HTML; ggplot2 + ggpubr + cowplot + binsreg + iplot for figures). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `WeightIt` / `gfoRmula` / `tmle` / `ltmle`, Mendelian randomization via `MendelianRandomization` / `TwoSampleMR` / `MRPRESSO`, KM / Cox / AFT / RMST survival via `survival` / `survminer` / `flexsurv`, E-value sensitivity via `EValue`, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `DoubleML`, S/T/X/R/DR meta-learners via `causalweight` / `grf`, causal forest via `grf::causal_forest`, BART/BCF via `bartCause` / `bcf`, matrix completion via `MCPanel`, CATE distribution + policy tree via `policytree`, off-policy evaluation, conformal causal via `conformalInference` / `cfcausal`, fairness audit via `fairmodels`, DAG learning via `pcalg` / `bnlearn` / LLM-assisted). Use when the user asks for a complete R empirical analysis, wants a tidyverse-style reproducible R script / Quarto workflow, prefers fixest over reghdfe, needs the R counterpart to StatsPAI / 00.1 / 00.2, or names a specific R step in isolation ("feols with cluster", "MatchIt nearest neighbor", "bacondecomp in R", "gtsummary table 1", "modelsummary to Word"). Mode A triggers on "target trial emulation R", "tmle ltmle", "MendelianRandomization", "TwoSampleMR", "MRPRESSO", "survival cox AFT", "STROBE R", "EValue R", "公共健康 R", "流行病学 R". Mode B triggers on "DoubleML R", "grf causal forest", "policytree", "bartCause bcf", "conformal causal R", "fairmodels", "pcalg NOTEARS", "因果机器学习 R".
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc + binscatter. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step Stata pipeline an applied economist runs on every paper — (1) data import & cleaning (use/import, destring, misstable, duplicates, merge assert), (2) variable construction (gen/egen/winsor2/xtile/xtset with L./F./D.), (3) descriptive statistics & Table 1 (tabstat/balancetable/asdoc), (4) classical diagnostic tests (sktest/swilk/hettest/imtest/xtserial/xttest3/vif/dfuller/kpss/hausman/estat overid), (5) baseline modeling (reg/xtreg/reghdfe/ivreg2/ivregress/csdid/did_imputation/eventstudyinteract/sdid/rdrobust/synth/psmatch2/teffects/heckman/qreg/ppmlhdfe), (6) robustness battery (bacondecomp/honestdid/rwolf/ritest/wildbootstrap/oster), (7) further analysis (subgroup/triple-diff/interactions/medsem/marginsplot/binscatter by group), (8) publication-ready tables & figures (esttab/outreg2/estout/coefplot/marginsplot/rdplot/twoway combined). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `teffects ipw` / `teffects ipwra` / `teffects aipw` / `eltmle`, Mendelian randomization via `mrrobust` (IVW / Egger / weighted median) and `mregger` / `mrpresso`, KM / Cox / AFT / RMST survival via `sts` / `stcox` / `streg` / `strmst2`, E-value sensitivity via `evalue` (Linden-Mathur), principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `ddml` / `pdslasso`, S/T/X/R/DR meta-learners via `crforest` and `ddml interactive`, causal forest via `crforest` / `cforest`, BART/BCF via `bart` / `bartCause`-style externals, CATE distribution + policy tree via `crforest`, off-policy evaluation, conformal causal externals, fairness audit, DAG learning via `pcalg` / external Python callouts). Use when the user asks for a complete Stata empirical analysis, wants a reproducible .do-file pipeline, needs a Stata counterpart to the Python StatsPAI / Full-empirical-analysis-skill, or names a specific Stata step in isolation ("run reghdfe with two-way clustering", "csdid event study", "winsor2 at 1%", "esttab to LaTeX", "coefplot with CI", "ivreg2 weak-IV test", "synth_runner placebos", "teffects psmatch balance check"). Mode A triggers on "target trial emulation Stata", "teffects ipw aipw", "eltmle", "mrrobust", "mregger weighted median", "stcox AFT survival", "strmst2", "evalue Stata", "STROBE Stata", "公共健康 Stata", "流行病学 Stata". Mode B triggers on "ddml Stata", "pdslasso", "crforest causal forest Stata", "policy tree Stata", "因果机器学习 Stata".
PROACTIVE SKILL — automatically apply whenever writing, generating, or editing any text that is mainly in Chinese. No user trigger needed. Also use when the user explicitly asks to "fix Chinese", "修改中文", "去翻译腔", "去AI味", "fix Chinese formatting", or "review Chinese text". Eliminates AI-sounding expressions and translation artifacts. Enforces Chinese-English mixed formatting rules (spacing, punctuation, bold formatting).
所有联网操作必须通过此 skill 处理,包括:搜索、网页抓取、登录后操作、网络交互等。触发场景:用户要求搜索信息、查看网页内容、访问需要登录的网站、操作网页界面、抓取社交媒体内容(小红书、微博、推特等)、读取动态渲染页面、以及任何需要真实浏览器环境的网络任务。
This skill should be used when the user asks to "/do-agent", asks for "Execute complex tasks using multi-agent architecture with context protection", or needs the workflow previously provided by the /do-agent slash command.
Access NBER working papers and economic research datasets
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
Find free legal full-text versions of scholarly articles via Unpaywall
Generate a complete academic literature survey from scratch using multi-agent orchestration. Searches academic databases (OpenAlex, CrossRef, Unpaywall), downloads PDFs, builds BibTeX, drafts a LaTeX review, compiles it, reviews for quality, and revises based on feedback — all automated. Use this skill whenever the user asks to "generate a literature review", "write a survey paper", "review recent papers on [topic]", "create a survey of [field]", "综述", "文献综述", "survey papers in top journals", or wants a multi-agent pipeline to produce a publishable-quality literature review. Also trigger when the user wants to search multiple journals for papers on a topic and synthesize findings into a structured document. Works for any academic field but optimized for economics journals.
Export Marp slide markdown files to PDF (default), HTML, PPTX, or PNG. Handles theme loading, Chrome/Chromium detection for PDF export, and batch conversion. Trigger when user says "export slides", "convert marp to pdf", "marp export", "slides to pdf", "slides to html", "导出slides", "slides转pdf", "导出演示文稿".
This skill should be used when the user asks to "search for academic papers", "find working papers on SSRN", "look up a DOI", "download paper PDF", "check open access availability", "search NBER papers", "find arXiv preprints", or "search CrossRef". Provides unified search, metadata retrieval, and PDF download across arXiv, NBER, SSRN, CrossRef, OpenAlex, Unpaywall, and Semantic Scholar. Covers economics, finance, social science, CS/AI, and all academic disciplines.
Econometrics skill for creating publication-quality LaTeX regression and summary tables. Activates when the user asks about: "regression table", "LaTeX table", "esttab", "stargazer", "modelsummary", "publication table", "format results", "multi-panel table", "journal table", "export regression results", "table formatting", "回归表格", "LaTeX表格", "结果导出", "论文表格", "回归结果格式化", "多模型表格"
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Convert English straight quotation marks ("...") to Chinese curved quotation marks ("..." U+201C/D). Use when processing Chinese text documents, markdown files, or any content that needs proper Chinese typography with directional quotes. Triggers on keywords like "转换引号", "中文引号", "英文引号转中文", "quote conversion", "convert quotes".
Econometrics skill for time series analysis. Activates when the user asks about: "time series", "stationarity", "unit root test", "ADF test", "KPSS test", "ARIMA", "ARMA", "autocorrelation", "ACF", "PACF", "VAR model", "VECM", "Granger causality", "cointegration", "impulse response function", "forecast", "seasonal decomposition", "ARCH", "GARCH", "时间序列", "平稳性检验", "单位根", "自回归", "格兰杰因果", "协整", "脉冲响应", "预测", "向量自回归"
经管 / 社科**实证论文全流程总编排器(meta-orchestrator)**:把「选题 → 设计 → 数据 → 计量识别与估计 → 表与图 → 写作初稿 → 全流程打磨 → 语言去 AI 味 → 模拟评审与修订 → 选刊与投稿 → 复盘交付」这条端到端流水线自动跑通。本 skill **不重复实现任何子能力**, 而是借鉴 `do-agent` 的「多代理 + 上下文保护」执行范式与 `paper-pipeline` 的「固定顺序 + 可断点续跑 + 交互档位」编排范式,按阶段**调用既有 skill / 派发并行 subagent** 完成一篇 可投稿的实证论文。触发场景:用户说 "/paper-workflow"、"帮我写一篇实证论文"、 "从选题到投稿"、"实证论文全流程"、"经管社科论文工作流"、"端到端跑一篇 paper"、 "automate an empirical paper"、"end-to-end empirical research pipeline"、"paper workflow", 或带着一个研究方向 / 一份计划书 / 一份数据 / 一份初稿希望「一条龙」推进到投稿。
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Convert Markdown files to Word documents (.docx) with proper formatting, Chinese font support (FangSong for all text including headings), black font color, 1.5x line spacing, precise first-line indent (24pt), heading spacing after (1 line), no italic headings, and automatic superscript conversion for citation numbers. Use when converting .md files to .docx, creating Word documents from markdown, or when user mentions Word, DOCX, or document conversion. Requires pandoc.
Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content.
Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
所有联网操作必须通过此 skill 处理,包括:搜索、网页抓取、登录后操作、网络交互等。触发场景:用户要求搜索信息、查看网页内容、访问需要登录的网站、操作网页界面、抓取社交媒体内容(小红书、微博、推特等)、读取动态渲染页面、以及任何需要真实浏览器环境的网络任务。
Deeply analyze any empirical economics PDF using the five-question framework (五问框架): research question, identification strategy, core estimand, robustness logic, and scholarly contribution. Converts the PDF to Markdown, dispatches 5 parallel sub-agents (one per question), then compiles a 2000–3000 Chinese-character report with a transferable methodology checklist. Optimized for empirical economics papers in top journals (AER, QJE, JPE, RFS, RoF, JFE, etc.). Use this skill whenever the user wants to: - systematically analyze an empirical economics paper - apply the 五问框架 (five-question framework) to a paper - extract transferable research design elements from a top-journal paper - understand a paper's identification strategy, estimand, or robustness logic - run /five-questions, /five-q, or /paper-five-q-analysis - "帮我做五问分析", "用五问框架分析这篇论文", "analyze this paper with the five-question framework"
Econometrics skill for Synthetic Control Method (SCM). Activates when the user asks about: "synthetic control", "SCM", "synthetic counterfactual", "donor pool", "placebo test", "in-space placebo", "in-time placebo", "MSPE ratio", "Abadie Diamond Hainmueller", "augmented synthetic control", "penalized SCM", "synthetic DID", "合成控制", "合成控制法", "捐助池", "安慰剂检验", "合成反事实", "合成DID", "政策评估"
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 20 community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code.
Econometrics skill for descriptive statistics and summary tables. Activates when the user asks about: "descriptive statistics", "summary statistics", "summary table", "Table 1", "balance table", "means and standard deviations", "correlation matrix", "data summary", "sample characteristics", "variable distributions", "描述性统计", "描述统计", "汇总统计", "统计表", "均值标准差", "平衡性检验", "相关矩阵", "样本特征", "变量分布"
根据研究者提供的**研究计划书(Research Proposal)**执行基于**外国(美国/欧盟/英国/日本/跨国)制度环境**的公司金融类实证研究全流程。**启动后第一件事:根据计划书的主题、识别策略、贡献边际与样本范围,从外国 CF 顶刊池(AER/QJE/JPE/JF/JFE/RFS/JFQA/JAR/JAE/MS/JCF/JBF 等 25+ 期刊)中推荐 5 本最匹配的目标期刊([J1]–[J5]),等待研究者明确选定一本;该期刊决定 main.tex 的 bibliographystyle、Section 骨架、Introduction 风格与表注规范**。然后用 Python 完成数据清洗、描述性统计、基准回归、内生性检验(IV/2SLS、DML)、平行趋势、异质性、机制、稳健性检验与图表绘制。LaTeX 表格和图像严格遵循 template/ 示例格式,研究逻辑与排版严格遵循 rule/ 下的《通用实证研究逻辑与规范总结》与《回归表写作规范总结》。数据集与政策集从 asset/ 中按计划书中的关键词检索(WRDS / NBER/Fed releases / FRED / 全球宏观库)。**当计划书预期的实证结果无法实现时(系数不显著、平行趋势不通过、IV 弱工具、机制不成立等),skill 自动切换备选方案直至完成研究项目**。最终交付物:Python 代码 + LaTeX 表格 + 图像(.pdf/.png)。触发条件:研究者提交研究计划书(含 X→Y 假设、识别策略、样本、政策冲击等)。
Upgrade of chinese-ppt for Chinese Beamer decks (xelatex + ctex + fandol, CUFE template). Same 7-section outline and X→M→Y framework, but adds (a) mandatory 1.3 line-spacing + 3pt paragraph spacing, (b) overflow-prevention line budget + balanced split-frame rules, (c) prose rewrites that strip AI-ish "关键比较/理论映射" labels and redundant 章节括号注释, (d) stricter CJK-space + middle-dot rules, (e) retrofit workflow for existing chinese-ppt decks, (f) mandatory local linespread reset inside TikZ / table / fixed-geometry frames. Use for "做中文学术PPT 2 版"、"中文 Beamer 改进版"、"答辩 PPT chinese-ppt2"、"防越界 PPT"等请求。用户在 Overleaf 编译,只产出 .tex + figures/,不要附加 compile 脚本。
Convert English straight quotation marks ("...") to Chinese curved quotation marks ("..." U+201C/D). Use when processing Chinese text documents, markdown files, or any content that needs proper Chinese typography with directional quotes. Triggers on keywords like "转换引号", "中文引号", "英文引号转中文", "quote conversion", "convert quotes".
Export Marp slide markdown files to PDF (default), HTML, PPTX, or PNG. Handles theme loading, Chrome/Chromium detection for PDF export, and batch conversion. Trigger when user says "export slides", "convert marp to pdf", "marp export", "slides to pdf", "slides to html", "导出slides", "slides转pdf", "导出演示文稿".
Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"
Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content.
金融经济学实证论文计划书生成器。根据用户提供的研究方向,生成包含标题、假说、数据来源、实证策略、 预期结果表格、稳健性检验、异质性分析、机制检验等12个完整模块的研究计划书。 内置中国微观/宏观数据库(皮皮侠1599个数据集、马克数据377个数据集)和WRDS国际数据库索引, 自动匹配可用数据源。融合Edmans (2024) "Learnings From 1000 Rejections"的编辑视角作为质量护栏, 确保选题具有真正的边际贡献而非"just another determinant of Y"。 当用户提到以下任何情境时触发:写研究计划书、research proposal、论文开题、选题+计划、 帮我设计一个实证研究、empirical research design、我想研究X对Y的影响怎么做、 帮我找个能发表的选题、generate proposal、写一个可以投稿的研究方案、 研究设计、identification strategy、DID/RDD/IV研究设计。 即使用户只是描述了一个经济金融现象并想知道"能不能做成论文",也应考虑使用此技能。
Fetch economic data from FRED, World Bank, BLS, OECD, and Yahoo Finance
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Clean and transform messy data for analysis in Python, R, or Stata
Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"
经济金融顶刊文献速递与选题建议生成器。通过RSS和网页抓取获取经济学、金融学、会计学顶级期刊的最新论文, 筛选公司金融相关文献,生成中文综述摘要和研究选题建议。 当用户提到"期刊速递"、"文献周报"、"论文速递"、"最新文献"、"journal digest"、"paper digest"、 "选题建议"、"研究选题"、"顶刊追踪"、"文献追踪"、"周报"时触发此技能。 即使用户只是说"帮我看看最近有什么新论文"或"最近顶刊发了什么",也应该触发。
Econometrics skill for generating publication-quality figures for top economics journals. Activates when the user asks about: "econometric figure", "publication figure", "journal figure", "AER figure", "QJE figure", "event study plot", "coefficient plot", "coefplot", "binned scatter", "binscatter", "RDD plot", "parallel trends plot", "kernel density", "distribution plot", "time series plot", "map", "figure formatting", "academic plot", "论文图表", "学术图", "系数图", "事件研究图", "散点图", "分布图", "趋势图", "回归可视化"
This skill should be used when the user asks to "/do-agent", asks for "Execute complex tasks using multi-agent architecture with context protection", or needs the workflow previously provided by the /do-agent slash command.
Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"
Parallel control variable combination search via Stata. Exhaustively searches all subsets of optional controls to find the combination that maximises |t| of the independent variable. Activates when user says: "控制变量搜索", "搜控制变量", "control variable search", "跑控制变量组合", "暴力搜索", "调控制变量".
Econometrics skill for machine learning methods in causal inference. Activates when the user asks about: "causal forest", "generalized random forest", "GRF", "double machine learning", "DML", "debiased machine learning", "LASSO for variable selection", "post-LASSO", "heterogeneous treatment effects", "CATE", "conditional average treatment effect", "BLP analysis", "CLAN analysis", "causal tree", "honest estimation", "因果森林", "双重机器学习", "异质性处理效应", "条件平均处理效应", "LASSO变量选择", "机器学习因果推断", "去偏机器学习"
Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.
根据研究者提供的**研究计划书(Research Proposal)**执行基于中国制度环境的公司金融类实证研究全流程。**启动后第一件事:根据计划书的主题、识别策略、贡献边际与样本范围,从中国-context 英文顶级期刊池(JF/JFE/RFS/JFQA/MS/JCF/JBF/JAR/JAE/TAR/CAR/JIBS/China Economic Review/PBFJ 等 25+ 期刊)中推荐 5 本最匹配的目标期刊([J1]–[J5]),等待研究者明确选定一本;该期刊决定 main.tex 的 bibliographystyle、Section 骨架、Introduction 风格与表注规范**。然后用 Python 完成数据清洗、描述性统计、基准回归、内生性检验(IV/2SLS、DML)、平行趋势、异质性、机制、稳健性检验与图表绘制。LaTeX 表格和图像严格遵循 template/ 示例格式,研究逻辑与排版严格遵循 rule/ 下的《通用实证研究逻辑与规范总结》与《回归表写作规范总结》。数据集与政策集从 asset/ 中按计划书中的关键词检索。**当计划书预期的实证结果无法实现时(系数不显著、平行趋势不通过、IV 弱工具、机制不成立等),skill 自动切换备选方案直至完成研究项目**。最终交付物:Python 代码 + LaTeX 表格 + 图像(.pdf/.png)。触发条件:研究者提交研究计划书(含 X→Y 假设、识别策略、样本、政策冲击等)。
Convert Markdown files to Word documents (.docx) with proper formatting, Chinese font support (FangSong for all text including headings), black font color, 1.5x line spacing, precise first-line indent (24pt), heading spacing after (1 line), no italic headings, and automatic superscript conversion for citation numbers. Use when converting .md files to .docx, creating Word documents from markdown, or when user mentions Word, DOCX, or document conversion. Requires pandoc.
Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"
PROACTIVE SKILL — automatically apply whenever writing, generating, or editing any text that is mainly in Chinese. No user trigger needed. Also use when the user explicitly asks to "fix Chinese", "修改中文", "去翻译腔", "去AI味", "fix Chinese formatting", or "review Chinese text". Eliminates AI-sounding expressions and translation artifacts. Enforces Chinese-English mixed formatting rules (spacing, punctuation, bold formatting).
Econometrics skill for instrumental variables and treatment effect estimation. Activates when the user asks about: "instrumental variables", "IV estimation", "2SLS", "two-stage least squares", "endogeneity", "weak instruments", "first stage", "Sargan test", "overidentification", "propensity score matching", "PSM", "average treatment effect", "ATT", "LATE", "local average treatment effect", "endogenous regressor", "instrument validity", "工具变量", "两阶段最小二乘", "内生性", "弱工具变量", "倾向得分匹配", "平均处理效应", "处理效应", "局部平均处理效应"
Generate, continue, revise, polish, and stress-test game theory research papers. Use when the user provides a game theory topic, phenomenon, draft, outline, model idea, literature anchor, reviewer comments, or asks for 博弈论论文生成, 选题建模, 文献迁移, 模型修正, 均衡分析, 数值模拟, 论文润色, 改稿打磨, or R&R response work.
Look up Stata command documentation and display formatted help text.
Run static analysis on a Stata .do or .ado file and report style and best-practice issues.
Improve, modernize, and optimize existing Stata code for performance, portability, and maintainability. Use when legacy patterns such as preserve/restore, cd,
Plan and critique power, MDE, and sample-size calculations for Stata-based research workflows. Use when the user is designing a study, checking detectability, or defending precision claims.
Run arbitrary Stata code or a .do file and display the result.
Review regression outputs, tables, and graphs for publication readiness. Use when the user asks whether a result is ready for a paper, appendix, seminar, referee response, or coauthor review.
Run replication, robustness, and specification-sensitivity workflows for Stata projects. Use when a researcher wants to reproduce a result, rerun a pipeline, compare specifications, audit a do-file sequence, or check whether a claim is stable.
Install, configure, update, or verify mcp-stata across Claude Code, Codex, Gemini CLI, Cursor, Windsurf, and VS Code. Activate when users ask to set up the Stata toolkit or troubleshoot the installation.
Fetch and display stored r(), e(), and s() results from the last Stata command.
Organize and execute Stata workflows for referee responses, robustness requests, and coauthor follow-ups. Use when the user needs to answer a critique with targeted reruns, tables, figures, and a defensible audit trail.
Show mcp-stata identity, connected tools, and status. Use when the user asks if mcp-stata is available, asks about access to the toolkit, or asks what Stata tools are connected.
Activate when users mention Stata commands, .do files, regressions, econometrics, stored results, graphs, dataset inspection, replication, or Stata errors. Route the task through mcp-stata tools and the specialized research skills instead of treating it as plain text coding.
Diagnose local Stata, MCP, package, startup, graph-export, and permissions issues. Use when setup is failing, Stata is not discovered, packages are missing, logs are truncated, or a managed machine behaves differently from a normal workstation.
Tail, read, or search a Stata log file from a previous command or background task.
Describe and summarize the current dataset in memory. Optionally inspect a specific variable with codebook.
List, export, and review Stata graphs from the current session.
Build and review paper-ready regression, balance, and summary tables from Stata outputs. Use when the user needs a clean table for a draft, appendix, or coauthor share-out.
Scaffold or audit a social-science replication package at a target directory. Generates folder structure, README, master.R, figure/table crosswalk, codebook template, LICENSE placeholder, and pre-release checklist. Adapted from Yusaku Horiuchi's replication-package-guide with FAIR-principle integration; platform-neutral (Harvard Dataverse, OSF, Zenodo, GitHub releases, institutional archives).
Modern tidyverse patterns for R including pipes, joins, grouping, purrr, and stringr. Use when writing tidyverse R code.
rlang metaprogramming patterns for data-masking, injection operators, and dynamic dots. Use when writing functions that use tidy evaluation.
Structured policy briefing note (1-2 pages). Issue, background, analysis, options, recommendation. UK GES, Australian Treasury, consulting formats. Auto-populates from econstack data skills.
Write pre-analysis plans: PAP structure, registry, analysis strategy.
Use when the user asks about academic literature, research papers, scholarly works, authors, citations, institutions, journals, or any academic metadata. Trigger when users want to search for papers, find author profiles, track citations, discover related works, or explore academic topics. Also use when users mention DOIs, ORCIDs, h-index, publication venues, or research metrics.
R package development guide covering dependencies, API design, testing, and documentation. Use when developing R packages.
Public finances briefing. Supports UK, US, and Australia. Produces a single compact briefing on borrowing, debt, receipts, spending, and fiscal rules. Optional debt sustainability analysis via the debtkit R package. User-selectable sub-components and multi-format export.
Brainstorm a longlist of benefits and costs for a project. Outputs two clean tables (benefits and costs), each with materiality (H/M/L), a cash flow tag (cash in / cash out / non-cash), a quantification method, and a monetisation method. Supports HMT Green Book, EU Better Regulation Guidelines, World Bank, Asian Development Bank, and the Victorian Treasury High Value High Risk (HVHR) framework.
Use when starting a new research project, exploring a research idea, deciding whether a question is viable, or before touching code or data for a new paper. Runs a research-focused brainstorm that clarifies research question, identification strategy, data feasibility, and contribution before any implementation.
Comprehensive exploratory data analysis with publication-quality descriptive tables, correlation matrices, distribution plots, and assumption testing. Generates a standalone EDA report with Table 1 (gtsummary/great_tables), correlation heatmap, distribution diagnostics, VIF for multicollinearity, and normality/homoscedasticity tests. All figures are APA-formatted and colorblind-safe. Use when the user says "exploratory analysis," "EDA," "descriptive statistics," "explore the data," "Table 1," "correlations," "distributions," or when /data-clean completes successfully. Triggers on "EDA," "descriptive," "Table 1," "explore," "correlations."
Cost-benefit analysis. Produces economic NPV and financial NPV side by side, with BCR, optimism bias (with mitigation), Marginal Excess Tax Burden, real-terms rebasing, WELLBY / QALY / VPF wellbeing valuation, sensitivity, switching values, EANC for unequal-life options, validation gate, and a one-line headline verdict (socially worthwhile vs financially self-sustaining). Backed by the greenbook R package (HM Treasury Green Book primitives) when available, with graceful fallback. Supports HMT Green Book, EU Better Regulation, World Bank, ADB, and Victorian HVHR. Reads a longlist markdown file directly via --from.
Audit economic analysis outputs (fiscal briefings, macro briefings, market research, longlists, and other quantitative economic documents) against methodology standards, academic literature, and common errors. Runs structured checks across core categories including counterfactual, additionality, discounting, double counting, distributional analysis, Aqua Book RIGOUR, and Flyvbjerg-style strategic misrepresentation detection. Returns a RAG scorecard with issues ranked by severity.
Query and analyze SEC filings using EdgarTools
Use when generating a LaTeX results table, creating a figure for a paper, formatting descriptive statistics, preparing regression output for publication, or producing vector-quality graphics. Enforces booktabs, threeparttable, vector PDFs, and script-generated output.
Use when a main specification has produced a result, when preparing a paper appendix, when a reviewer requests robustness, or before declaring any empirical finding final. Guides selection of design-appropriate checks without mandating a fixed checklist.
Use when drafting, rewriting, reviewing, or auditing prose for any section of an empirical academic paper (Abstract, Introduction, Methods, Data, Results, Discussion, Conclusion) or specialized output (job market paper, grant proposal, policy brief, referee response).
Use when a research design spec exists and the user is ready to translate it into a concrete implementation plan with phased tasks, artifacts, and verification criteria. Produces a research execution plan organized in canonical research phases — collection, preparation, analysis, robustness, writing, submission.
Use when choosing a target journal for a paper, comparing journal rankings, asking "where should I submit this", or building a submission strategy across multiple journals. Field-agnostic — detects the paper's research area and suggests appropriate outlets across tiers.
Use when preparing a paper for submission to a specific journal, checking formatting requirements, parsing instructions for authors, building a submission checklist, or adapting a paper to a journal template. Fetches the journal's official guidelines via web and produces a verifiable checklist.
Bidirectional review — THE entry point for every research engagement. Reviews everything the researcher has (data, docs, code, instruments) and produces two outputs: (1) a gap analysis showing what their project needs to meet gold standards, and (2) suite-learning findings identifying what our skill suite can learn from what they brought. Runs at the START of every engagement and in lighter form at session END. Use when the user says "I have data," "review what I have," "where do I start," "look at my project," "what am I missing," or at the beginning of any research engagement. Also triggers on "intake," "gap analysis," "audit my materials," "what should I improve."
Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.
Run declarative data quality checks and generate a codebook. Checks completeness, distributions, impossible values, duplicates, outliers, encoding issues, attention check failures, and manipulation check results. Produces a pointblank/pandera validation report and an auto-generated codebook. Use when the user says "validate data," "check data quality," "generate codebook," "what's wrong with my data," "data audit," "check my dataset," or when /research-intake identifies missing validation. Triggers on "validate," "data quality," "codebook," "check my data."
Generate a complete, manuscript-ready data profile: demographics summary table, scale identification with reliability (alpha, omega, CFA), comprehensive codebook, sample characteristics, and measurement documentation — all following current best practices at the time of execution. Searches for the latest reporting standards (JARS, TOP, APA) before generating output. Produces everything a Methods section needs to describe the data. Use when the user says "describe my data for the manuscript," "demographics table," "what scales are in here," "codebook," "Methods section data," "sample characteristics," or any time they need data documented for publication. Triggers on "profile," "demographics," "scales," "codebook," "sample description," "Methods section."
Create publication-quality figures that meet journal submission standards. APA 7th defaults with journal-specific overrides. Supports interaction plots, mediation path diagrams, forest plots, marginal effects, Johnson-Neyman plots, correlation heatmaps, and coefficient plots. All figures are colorblind-safe, high DPI, and exported in multiple formats (PDF, PNG, SVG, TIFF). Use when the user says "publication figures," "journal figures," "APA figures," "visualize results," "make plots," "interaction plot," "path diagram," "forest plot," or when /analyze or /process-model or /robustness completes. Triggers on "visualize," "figure," "plot," "diagram."
Scaffold a new research project with full reproducibility infrastructure in R and/or Python. Creates directory structure, pipeline stubs (targets/Snakemake), environment lockfiles (renv/uv), documentation templates (codebook, decision log, pre-registration, Cornell README), Quarto manuscript template, and proper .gitignore. Can wrap existing data in gold-standard structure. Use when the user says "new project," "scaffold," "start a study," "set up a project," "I have data and need to organize it," or when /research-intake recommends scaffolding.
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
Industry and market research. Market sizing, structure, competition, regulation, supply chains, pricing, M&A. Produces a single compact, source-cited research report with Porter's Five Forces, HHI / CR4, PESTLE, and trade flows. Supports UK, US, EU, Australia, and global scope, with multi-geography comparison.
Verify academic citations against CrossRef, Semantic Scholar, and OpenAlex. Detects AI-hallucinated references, chimeric citations, and suspicious patterns.
Design conjoint experiments: attributes, power, AMCE/AMIE estimation.
Audit figures, tables, captions, cross-references, and statistical notes.
Clean and reshape Qualtrics conjoint exports to analysis-ready long format.
Pre-submission audit: argument, numerics, refs, writing, figures, replication.
Structural topic modeling: STM spec, topic count, coherence-exclusivity.
Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data. Guides the process (assumptions, estimation, reporting, diagnostics) without forcing a fixed method list.
Use when working on any empirical academic research context — paper writing, data analysis, literature review, or any task involving citations, results, or publication artifacts. Establishes non-negotiable principles that govern all other superpapers skills.
Audit manuscript and replication package against FAIR open-science principles.
Causal inference framework for answering "does X cause Y?" beyond correlation. DoWhy (Microsoft Research) provides the identify-estimate-refute loop: define a causal graph (DAG), identify the causal effect using backdoor/frontdoor/instrumental variable criteria, estimate treatment effects with multiple estimators, and validate results with automated refutation tests. Use when: distinguishing causation from correlation, estimating treatment effects (ATE, ATT, CATE), designing and analyzing A/B tests with confounders, using instrumental variables, performing counterfactual reasoning ("what would have happened if..."), validating causal claims with sensitivity analysis, working with observational data where randomization is impossible, or any analysis where the question is "what is the CAUSAL effect of X on Y" rather than just "how do X and Y relate?"
Draft scientific introductions: argument logic, framing, multi-experiment coherence.
Use when a research implementation plan exists in docs/superpapers/plans/ and the user is ready to execute it — collecting data, running analysis, producing outputs, writing the paper. Orchestrates task execution with replication-driven verification and two-stage review at phase boundaries.
Use when compiling a LaTeX paper, debugging LaTeX errors, building a paper PDF, or when a .tex file fails to produce output. Handles engine detection (xelatex vs pdflatex), bibliography systems (biber vs bibtex), and multi-pass compilation.
Use when starting empirical analysis, creating a data pipeline, generating results, or when data or model specifications change. Enforces end-to-end reproducibility — every number in the paper must be regenerable from raw data by a script with a fixed seed. Replaces TDD for the research domain.
Design, run, and critique causal inference workflows in Stata. Use when the user is working on identification, treatment effects, DiD, IV, event studies, RD, or assumption-sensitive empirical claims.
Audit datasets for structure, missingness, labeling, suspicious values, duplicate identifiers, and documentation readiness. Use when a researcher asks for data QA, codebook review, sanity checks, or pre-analysis cleanup guidance.
Track dataset lineage, transformation steps, merge logic, and reproducibility risks in Stata workflows. Use when the user needs to explain where data came from, how it changed, or why a pipeline can be trusted.
Implement Hayes PROCESS mediation and moderation models transparently via lavaan and bruceR, with bootstrap CIs, index of moderated mediation, Johnson-Neyman regions of significance, and APA-formatted output that matches familiar PROCESS tables. Maps model numbers (1-24) to inspectable lavaan syntax instead of black-box macros. Use when the user says "PROCESS model," "mediation," "moderated mediation," "conditional indirect effect," "Hayes model," "indirect effect," "moderation," or when /analyze encounters a mediation/moderation hypothesis. Triggers on "PROCESS," "mediation," "moderation," "indirect effect," "Hayes."
Build or audit a literature review: evidence map, gaps, synthesis plan.
Design and format publication-quality figures: chart choice, color, scales, legends, captions, reproducibility.
Build falsifiable causal hypotheses: DAGs, FPCI, equivalence testing.
Check methods reporting against CONSORT, JARS, DA-RT standards.
VLM-based OCR pipeline: model selection, prompts, architecture, evaluation.
R object-oriented programming guide for S7, S3, S4, and vctrs. Use when designing R classes or choosing an OOP system.
Macroeconomic monitor. Supports UK, US, Euro area, and Australia. Pulls GDP, inflation, employment, wages, rates, trade, housing, and fiscal data. Each country follows its central bank's reporting structure. Produces a single clean briefing with a traffic-light assessment and user-selectable sub-components.
Draft a senior peer-review report on a social-science manuscript.
Clean post-OCR text: correction, QA, multilingual handling, provenance.
Diagnose conjoint design integrity, estimation choices, and validity.
Design and format publication-quality tables: column order, row grouping, notes, precision, reproducibility.
Design cross-national survey experiments: power, equivalence, localization.
Use when the user asks to search for papers, review literature, find references on a topic, verify a paper exists, or build a bibliography. Enforces web verification of every citation via web fetch to prevent hallucinated references.
Use when adding citations to a .bib file, importing references by DOI, cleaning a bibliography, detecting duplicate entries, or normalizing citation keys. Uses direct .bib manipulation with CrossRef API for metadata resolution — no external tool dependencies.
LLM-based text classification: codebook, validation, agreement statistics.
Confirmatory hypothesis testing matched to pre-registration, with full assumption testing, effect sizes, confidence intervals, and APA 7th formatted output. Supports OLS/GLM regression, panel regression (fixest), mixed models (lme4), SEM/CFA (lavaan), meta-analysis (metafor), and delegates PROCESS models to /process-model. Reads pre-registration to align planned analyses, flags deviations, and generates decision log entries for post-hoc choices. Use when the user says "test hypotheses," "run analysis," "confirmatory," "regression," "SEM," "mediation," "mixed model," "meta-analysis," or when /eda completes. Triggers on "analyze," "hypothesis," "regression," "model," "test."
Before implementing, generate 3-5 conceptually distinct approaches labeled by creativity dimension (Novel, Surprising, Diverse, Conventional), then hold for selection. Brainstorm-then-select to resist defaulting to the most obvious solution.
R performance best practices including profiling, benchmarking, vctrs, and optimization strategies. Use when optimizing R code.
Design and diagnose list experiments (item count technique).
Produce documented data cleaning scripts that log every transformation with N before/after each step, generate a CONSORT-style exclusion flow diagram, create decision log entries for every subjective choice, compute scale reliability and composites, and write cleaned data to data/processed/. Never modifies raw data. Use when the user says "clean data," "prepare data," "apply exclusion criteria," "handle missing data," "create composites," "data preprocessing," or when /data-validate found issues to address. Triggers on "clean," "exclusion," "missing data," "preprocessing," "composites," "reverse code."
Patterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when performing Bayesian analysis.
Use when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source. Handles source discovery, respectful collection, local caching, and manifest documentation.
Audit in-text/reference parity, DOIs, claim support, and citation style.
Complete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.
R style guide covering naming conventions, spacing, layout, and function design best practices. Use when writing R code.
Test-driven development workflow for R using testthat. Use when writing new features, fixing bugs, or refactoring code. Enforces test-first development with 80%+ coverage.
Design survey instruments: questions, scales, flow, social desirability.
Expert economics paper writing assistant synthesizing advice from 50+ top guides by Cochrane, McCloskey, Shapiro, Head, Bellemare, Goldin, Glaeser, Kremer, and other leading economists. USE THIS SKILL whenever the user writes, edits, reviews, rewrites, or structures any economics paper, thesis, job market paper, abstract, introduction, conclusion, results section, literature review, or referee response. Also handles LaTeX formatting, presentations, and paper audits. Covers all paper types (applied, theory, structural, mixed) and all sections.
Start a new research project by conducting a structured interview to formalize a research idea, then generates research questions with identification strategies and a project spec. Make sure to use this skill whenever the user wants to develop or document a new research idea — not to search for literature or data. Triggers include: "new project", "start research", "I have an idea", "help me develop this", "I want to study X", "help me formalize this idea", "what's my research question", "what identification strategy should I use", "write up my project idea", or when the user describes a topic they want to turn into a paper.
Guide to Zotero MCP for connecting Zotero library with AI assistants
TikZ and PGFPlots techniques for publication-quality scientific figures
Use grammar and style checking tools to polish academic manuscripts
Remove AI-generated patterns to produce natural, authentic academic writing
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.
Choose the appropriate CausalPy experiment class from a causal question, data structure, treatment assignment, and identification assumptions. Use before writing analysis code when the method is not yet settled.
Manage references with BibLaTeX, natbib, and LaTeX bibliography styles
LaTeX thesis template supporting multiple universities and formats
Write Tsinghua University theses using the ThuThesis LaTeX template
Guide to creating academic presentations with LaTeX Beamer
LaTeX template for arXiv preprints in NIPS/NeurIPS style format
Structure and write comprehensive literature reviews for any field
9 editing & proofreading skills. Trigger: polishing drafts, academic tone, proofreading, translation. Design: style checkers and editing workflows for clear, concise academic English.
Templates and formatting guides for major academic conference submissions
Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC score", "make text human-like", "去ai化", "改成人话", "去机器味", "降低AI率", "过AIGC检测", "长文本改写", "小说改写"
Eliminate wordiness and redundancy in academic prose for clarity
Write ML/AI research papers targeting NeurIPS, ICML, and ICLR venues
Comprehensive guide to LaTeX editors, packages, and typesetting workflows
Use plagiarism detection tools and ensure manuscript originality
Set up LaTeX templates for PhD and Master's thesis documents
Guide for writing formal academic papers following IEEE and ACM standards
Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature. Detects and fixes patterns including: inflated significance claims, superficial -ing analyses, vague attributions, AI vocabulary words, copula avoidance, excessive hedging, generic conclusions, informal word choices (linked/beyond/via/where/yield), overly assertive causal claims, and artificially condensed expressions. Preserves legitimate academic transitions (Notably, Prior studies have shown, etc.).
Curated tools and techniques for scientific writing beyond LaTeX
Write effective point-by-point responses to peer reviewer comments for revisions
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
Beautiful LaTeX template for working papers and technical reports
Review and polish LaTeX research papers for clarity and style
Validate bibliography entries against citations in all source files. Find missing entries and unused references. Make sure to use this skill whenever the user has any concern about bibliography completeness or citation keys. Triggers include: "validate my bib", "check my citations", "find missing references", "I'm getting undefined citation errors", "are all my citations in the bib file", "check for unused references", "my bibliography is broken", "missing bib entries", "citation not found", or after adding new references from a lit review or before submission.
11 academic writing skills. Trigger: writing paper sections, structuring arguments, academic prose. Design: section-by-section guides (abstract, intro, methods, discussion) with templates.
Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.
LaTeX drawing examples for Bayesian networks, tensors, and diagrams
Guide to writing effective research paper introductions
Curated tools and resources for effective scientific writing
Guide to Zotero Better Notes for comprehensive note-taking in research
Transform AI-generated Chinese text into natural academic writing style
Guide to ZotFile for Zotero attachment management, renaming, and syncing
Write effective discussion sections that interpret results and impact
Craft structured research abstracts that maximize clarity and journal acceptance
Checklist-driven academic English polishing and Chinglish correction
Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
Draft a full academic paper manuscript from analysis outputs, project spec, and lit review. Make sure to use this skill whenever the user wants to turn completed analysis into a written paper — not to run analysis or review existing writing. Triggers include: "write the paper", "draft the manuscript", "write up the results", "start the paper", "turn my results into a paper", "write the introduction", "draft the empirics section", "I have my results, now write the paper", "help me write this up", "write the abstract", or any request to produce academic prose from existing research outputs.
Adjust writing tone and register for academic audiences and venues
11 latex skills. Trigger: LaTeX typesetting, formatting papers, mathematical notation, Beamer. Design: template-based guides with package recommendations and compilation tips.
Find and assess datasets for a research question. Dispatches Explorer agents to search across data source categories, then Explorer-Critic to stress-test each candidate. Produces a ranked list with feasibility grades. Make sure to use this skill whenever the user wants to identify or evaluate data sources — not to search for papers or run analysis. Triggers include: "find data", "what data should I use", "find a dataset for this", "where can I get data on X", "assess datasets", "what datasets exist for", "help me find data", "is there data on this", "what are my data options", "I need data for this project", or any request to locate empirical data sources for a research question.
Guide to Zotero GPT for AI-powered research assistance within Zotero
Interactive setup wizard that configures a new project for the social-science-research plugin. Asks the user questions about their field, institution, journals, datasets, key researchers, and R color palette, then writes the answers into references/domain-profile.md and CLAUDE.md. Make sure to use this skill first whenever a user is starting fresh or wants to configure the plugin. Triggers include: "set up my project", "configure the plugin", "run setup", "initialize this project", "I just installed the plugin", "set my field", "set my institution", "configure my domain profile", or any request to personalize the plugin for a specific research context.
Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files. Make sure to use this skill whenever the user wants their existing R code evaluated or audited — not when they want new analysis written. Triggers include: "review my R script", "check my R code", "is my code replication-ready", "audit this R file", "does this code follow conventions", "will this reproduce", "check my analysis script", "code review", "review-r", or when the user has an existing .R file and wants quality feedback rather than new code.
LaTeX-based academic writing assistant for thesis and paper templates
Opinionated Bayesian modeling workflow with PyMC and ArviZ. Contains critical guardrails (nutpie sampler, prior/posterior predictive checks, LOO-PIT calibration, prior sensitivity checks, 94% HDI, non-centered parameterizations, reproducible seeds) that agents won't apply unprompted — always consult before writing Bayesian model code. Trigger on: building probabilistic/Bayesian models, prior elicitation, MCMC inference, convergence diagnostics (divergences, R-hat, ESS), model comparison (LOO-CV, ELPD, stacking weights), hierarchical/multilevel models, count regressions, logistic regression with uncertainty, prior sensitivity analysis, reporting Bayesian results, or mentions of PyMC, ArviZ, InferenceData, credible intervals, posterior distributions, shrinkage, uncertainty quantification. Also trigger for model comparison, diagnosing sampling problems, choosing priors, or presenting stats to non-technical audiences.
Defamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.
Convert Markdown to publication-quality PDF with LaTeX math rendering
Structured literature review using a parallel fleet of Librarian agents. Searches top journals, working paper repositories (NBER, SSRN, IZA), and traces citation chains from key papers. Make sure to use this skill whenever the user wants to survey existing research on a topic — not to find datasets or write a paper. Triggers include: "review the literature", "find related papers", "what's been done on X", "search for papers on", "do a lit review", "find papers about", "what papers should I cite", "who has written about this", "survey the literature", "find prior work on", or any request to locate and summarize academic publications on a topic.
Verify that every quantitative claim in the paper is traceable to an analysis output file, and that no important output was omitted. Make sure to use this skill whenever the user wants to check that the paper and analysis are consistent before submission. Triggers include: "run the quality gate", "check the paper matches the analysis", "verify consistency", "does the paper match my results", "check my numbers", "are my tables right", "quality check before submission", "verify my claims", "make sure everything is consistent", "double-check the paper against my output files", or any pre-submission integrity check between paper text and computed results.
Guide to Better BibTeX for Zotero for LaTeX and BibTeX workflows
PDF references add-on for enriching Zotero library metadata
Create SVG graphical abstracts for journal paper submissions
11 paper templates skills. Trigger: starting a new paper, formatting for submission, venue-specific layouts. Design: ready-to-use templates for arXiv preprint, conferences, thesis, and posters.
Guide to collaborative LaTeX editing with Overleaf
Collection of LaTeX templates for papers, presentations, and CVs
End-to-end data analysis workflow in R or Python — from exploration through regression to publication-ready tables and figures. Make sure to use this skill whenever the user wants to run any empirical analysis, write analysis code, or produce output from data. Triggers include: "analyze this data", "run a regression", "write R code for this", "write Python code for this", "I have a dataset", "help me with this regression", "run a DiD", "run an RDD", "event study", "IV regression", "fit a model", "produce a table", "make a figure", "explore my data", or any request involving a dataset path or empirical estimation.
Academic translation, post-editing, and Chinglish correction guide
面向中文学术论文的降 AIGC 检测率 Skill。针对知网、万方、维普、Turnitin 中文版的检测机制,识别并消除中文大语言模型的 17 类结构化写作痕迹。采用"定位 → 诊断 → 改写 → 自评 → 复查"五步闭环工作流,分章节差异化策略(摘要/引言/文献综述/方法/结果/讨论/结论),保持学术严谨性前提下通过检测。
Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.
Render LaTeX math expressions to images in PNG, JPEG, and SVG
LaTeX math typesetting, equation formatting, and cross-referencing
Guide to writing clear and reproducible methodology sections
Save papers with metadata to Zotero via its API programmatically
Write SJTU theses using the SJTUThesis LaTeX template with full compliance
Export Zotero items and annotations to Markdown note files
Create publication-quality scientific diagrams with TikZ in LaTeX
Run the proofreading protocol on academic writing — papers or manuscripts. Checks grammar, typos, layout issues, consistency, and academic writing quality. Produces a report without editing files. Make sure to use this skill whenever the user wants surface-level writing errors found — not substantive academic critique. Triggers include: "proofread", "check for typos", "grammar check", "look for errors in my draft", "proofread all", "polish this", "check my writing", "are there any mistakes", "proofread before I send this", or when the user wants a clean-up pass rather than feedback on arguments or methods.
Generate publication-ready scientific article PDFs from templates
Comprehensive manuscript review covering argument structure, econometric specification, citation completeness, and potential referee objections. Make sure to use this skill whenever the user wants substantive academic feedback on a paper — not just surface edits. Triggers include: "review my paper", "give me feedback on this draft", "what would a referee say", "anticipate referee objections", "act as a referee", "check my identification strategy", "is my argument convincing", "review this manuscript", "critique my paper", "will this pass review", or any request for deep critique of academic writing beyond typos and grammar.
Deep consistency audit of the entire repository — launches 4 parallel specialist agents to find factual errors, code bugs, broken references, count mismatches, and cross-document inconsistencies, then fixes all issues and loops until clean. Make sure to use this skill whenever the user wants a comprehensive repository-wide check — not a targeted review of a single file. Triggers include: "audit", "deep audit", "find inconsistencies", "check everything", "run a full audit", "are there any broken references", "check the whole repo", "something feels off", "run the audit loop", or after making broad changes across multiple files.
AI-powered scientific writing workflow from outline to polished draft
Templates, formatting rules, and strategies for thesis and dissertation writing
Audit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a detection-only mode that flags patterns without rewriting.
8 peer review skills. Trigger: reviewing manuscripts, comparing papers, quality assessment. Design: systematic review criteria, evaluation rubrics, and automated review tools.
Secure sandboxed code execution environments for reproducible research computing
Automate systematic literature reviews with LatteReview AI agents
Compare Zotero, Mendeley, EndNote, and Paperpile for research use
Clean, format, deduplicate, and manage BibTeX bibliography files for LaTeX
AI plugin for Zotero with ChatGPT, Claude, and DeepSeek support
Download datasets, manage competitions and notebooks via Kaggle API
Craft effective point-by-point reviewer response letters
Ethical web scraping and API-based data collection for research
Run and manage Google Colab notebooks for Python and ML research
Design rigorous experiments using DOE, factorial designs, and response surfaces
Design and conduct action research and participatory studies
Apply grounded theory methodology to develop theory from data
13 research methodology skills. Trigger: study design, methodology selection, scientific reasoning, mentoring. Design: rigorous methods frameworks covering qualitative, quantitative, and mixed approaches.
Design complex multi-diagram architectures using advanced Mermaid syntax
Guide to designing and conducting mixed methods research
Plan and manage systematic literature reviews with Parsifal platform
Design and conduct qualitative research using grounded theory and case studies
Build a persistent cross-session knowledge base from academic papers
Generate research ideas from collected papers with gap analysis
Tools and pipelines for automating systematic literature reviews
AI-assisted peer review tools, workflows, and quality standards
Structured framework for writing peer review reports and paper critiques
Write effective rebuttals to reviewer comments for journal submissions
Write literature reviews and survey papers from collected papers
Best practices for computational research notebooks with reproducible workflows
7 code execution skills. Trigger: running code, interactive notebooks, Jupyter, Colab, sandboxed execution. Design: execution environment guides with setup instructions and best practices.
Sync and manage Overleaf LaTeX projects from the command line
Reproducible Python environments, notebooks, and literate programming
Create reproducible research workflows with R and RMarkdown/Quarto
Convert Python, JavaScript, and TypeScript functions into Mermaid flowcharts
Generate hand-drawn style Excalidraw diagrams from text descriptions
Guide to JSON Crack for visualizing complex JSON data structures
Guide to tldraw for infinite canvas whiteboarding and diagram creation
Extract structured text, metadata, and references from academic PDFs
Split and read long documents chapter-by-chapter for structured analysis
10 document processing skills. Trigger: extracting text from PDFs, parsing references, document Q&A. Design: parsing pipelines (GROBID, marker) and structured extraction tools.
9 knowledge graphs skills. Trigger: building knowledge graphs, connecting concepts, ontology design. Design: graph construction, traversal, and visualization for research knowledge.
Design ontologies and knowledge graphs for research data modeling
RAG architecture for academic knowledge retrieval and synthesis
Translate scientific PDFs with preserved math formatting via PDFMathTranslate
Apply handwriting OCR to digitize historical and archival documents
Search and download research datasets from Kaggle, HuggingFace, and repos
Scrape web data ethically and legally for research purposes
22 citation management skills. Trigger: managing references, formatting citations, BibTeX, bibliographies. Design: reference manager integrations and citation style guides (APA, IEEE, etc.).
Build research knowledge graphs for literature synthesis and RAG systems
Plugin marketplace and discovery platform for Zotero
Deep dual-mode reading of academic papers from PDF or URL sources
PDF parsing, text extraction, and document format conversion
Feature-rich Zotero plugin for UI customization and styling
Generate structured concept maps from academic texts automatically
Deploy DocsGPT for private document analysis and research knowledge bases
Ready-to-use agent skills for scientific research and engineering
Sync Zotero references and annotations to Notion databases
Access Open Science Framework for preregistrations, preprints, and data
Sync Zotero references to Obsidian and Logseq markdown
7 ocr & translation skills. Trigger: scanning documents, recognizing formulas, translating academic papers. Design: specialized OCR (LaTeX, handwriting) and translation for scholarly content.
Extract and convert mathematical formulas from images and PDFs to LaTeX code
Strategies for translating academic papers while preserving technical accuracy
PDF Chinese translation plugin for Zotero reference manager
Guide to Zotero PDF Translate for multilingual PDF and annotation translation
Ant Group knowledge graph engine with SPG and KAG framework
Manage academic citations across BibTeX, APA, MLA, and Chicago formats
Guide to JabRef open-source BibTeX and BibLaTeX reference manager
Ethical Google Scholar data collection techniques and best practices
APA, MLA, Chicago citation format guide with CSL configuration
Guide to Jasminum for retrieving CNKI Chinese academic metadata in Zotero
Guide to Papis command-line document and bibliography manager for researchers
AI toolkit to parse, complete, and format academic references
Build and analyze citation networks from academic reference data
Manage references and search Mendeley's catalog via REST API
Generate diagrams from text via Kroki's multi-format rendering API
AI-assisted paper reading, PDF Q&A, and summarization workflows
Translate LaTeX documents preserving math formulas and structure
Insert citations and notes from Zotero into Obsidian knowledge bases
Dark mode theme plugin for Zotero reference manager
Simulate human research communities with multi-agent AI collaboration
Create UML diagrams and architecture visualizations with PlantUML
Write academic papers in Markdown with Pandoc for multi-format output
9 diagrams & visuals skills. Trigger: creating diagrams, flowcharts, architecture visuals, LaTeX drawings. Design: tool-specific guides (Mermaid, Excalidraw, TikZ) with academic conventions.
Harvest metadata from open repositories using OAI-PMH protocol
Create graphical abstracts, schematic diagrams, and scientific illustrations
Create flowcharts, sequence diagrams, and architecture diagrams with Mermaid
Build real-time knowledge graphs for AI agents using Graphiti by Zep
Claude Code skill for citation workflow via OpenAlex and CrossRef
Citation plugin for Obsidian note-taking with BibTeX support
Practical advice for thriving in PhD programs and academic research
Guide to EasySpider for visual no-code web data collection
Conduct thorough, constructive peer reviews and evaluate research papers
6 web scraping & data collection skills. Trigger: collecting web data, finding datasets, API access for research. Design: ethical scraping methods with rate limiting and data quality checks.
Citation reference parser using machine learning
Reference management library and collections API
Look up researcher profiles and academic identities via the ORCID registry
Track research impact beyond citations via PlumX altmetrics API
Claude Code-driven autonomous AI Scientist for discovery
Discover open access research outputs via the SHARE notification API
Analyze citation networks, impact metrics, and bibliometric patterns
Set up and leverage ORCID for researcher identification and profiles
Search and retrieve preprints from the arXiv open-access repository
Query open citation data and reference networks via OpenCitations
10 research automation skills. Trigger: automating experiments, tracking results, reproducible pipelines. Design: ML experiment management, workflow orchestration, and lab automation tools.
Search 300M+ scholarly and patent records via the Lens.org API
Understanding and calculating research impact metrics
Understand journal impact factors, h5-index, CiteScore, and SJR
Resolve DOIs and retrieve publication metadata from CrossRef registry
Search and access book metadata via the Open Library API
Open research repository for all disciplines
Process and analyze arXiv papers systematically for research workflows
31 database search skills. Trigger: finding papers, search strategies, querying academic databases. Design: one skill per database/tool with API details, query syntax, and rate limits.
Automate repetitive research tasks with pipelines, schedulers, and scripting
Guide to altmetrics and research impact beyond traditional citations
Pre-registration, open data, and FAIR principles for research
13 deep research & systematic reviews skills. Trigger: systematic reviews, multi-source synthesis, comprehensive literature surveys. Design: multi-step research protocols with quality assessment and evidence grading.
Retrieve structured metadata from any DOI via HTTP content negotiation
Conduct qualitative meta-synthesis and evidence synthesis methods
AI-driven multi-agent research assistant for end-to-end studies
Navigate NSF grant applications, program selection, and strategies
Transform research papers into interactive AI agents for exploration
Search NIH-funded grants and research projects via RePORTER API
Write competitive research proposals with clear objectives and budgets
Prepare and justify research grant budgets across funding agencies
Research data sharing and repository
Navigate EU Horizon Europe funding programs and proposal writing
Autonomous agent for comprehensive deep research on any topic
DOI content negotiation and metadata retrieval techniques
Open-source deep research agent by Alibaba for scholarly research
Systematic review methodology with PRISMA and evidence synthesis
Track and compare research experiments with Aim experiment tracker
Scoping review methodology for broad evidence mapping
Reference manager with PDF viewer and Markdown note support
Open pipeline for generating deep research trajectories with LLMs
Deep research agent searching 10+ sources with local or cloud LLMs
Survey of LLM agents for biomedical scientific discovery
AI second brain for deep research and personal knowledge management
Structured methodology for conducting exhaustive multi-source investigations
Open deep research alternative for private data with vector search
Automated deep research tool for thorough topic investigation
Microsoft AI-driven R&D agent for automated data and model development
Build reproducible data science pipelines with Kedro for research projects
Claude Code template for LaTeX, Beamer, and R research workflows
Automated scientific discovery via agentic tree search by Sakana AI
Search the world's largest library catalog via OCLC WorldCat API
Construct rigorous systematic search strategies for literature reviews
Search biomedical literature and retrieve records via PubMed E-utilities
Search EU-funded research outputs via the OpenAIRE Graph API
Self-hosted semantic search and text mining platform
Navigate MeSH vocabulary for precise PubMed and MEDLINE searches
Search IEEE's 6M+ engineering and CS publications via the Xplore API
Advanced Google Scholar search techniques for comprehensive literature discovery
Search multiple academic databases simultaneously with Findpapers
Search biomedical and life sciences literature via Europe PMC
Multi-source exhaustive literature search across academic databases
Compare major academic databases and when to use each for research
Automate survey deployment, data collection, and pipeline management
Search 2M+ education research records via the ERIC database API
Resolve dataset DOIs and query research data metadata via DataCite
Search computer science literature via the CiteSeerX digital library
Forward and backward citation chaining techniques for literature search
Use ChatPaper to summarize and search arXiv papers with LLM assistance
Master Boolean operators and advanced search syntax for academic databases
Search 400M+ open access documents via the BASE search engine API
Using Baidu Scholar for Chinese and English academic literature search
Zotero utility plugin for keyboard shortcuts and batch editing
Zotero workflow automation with custom actions and tags
Detect and manage duplicate items in Zotero libraries
Identify and link research organizations via the ROR registry API
Query Wikidata SPARQL for scholarly metadata, authors, and entities
9 grants & funding skills. Trigger: grant applications, funding search, budget planning, data repositories. Design: funder-specific guides with eligibility, submission requirements, and timelines.
Query the OpenAlex catalog of scholarly works, authors, and institutions
24 metadata & bibliometrics skills. Trigger: DOI resolution, citation metrics, author disambiguation, bibliometrics. Design: metadata APIs and bibliometric analysis tools for scholarly records.
Access Latin American and developing world research via SciELO API
Batch search and report generation from arXiv preprint repository
Search PLOS open access journals with full-text Solr-powered API
Perform science mapping and bibliometric analysis with R bibliometrix
Intelligent companion for ML engineering with arXiv integration
Search NSF awards and grants with free public API, no auth required
Zotero plugin for automatic attachment file organization
Disambiguate author identities via the VIAF authority file API
Search papers and analyze citation graphs via OpenAlex and CrossRef APIs
Query the Open Research Knowledge Graph for structured research data
Summarize academic papers with structured extraction of key elements
Track scholarly mentions across the web via Crossref Event Data
Command-line tools for searching and batch-downloading arXiv papers
Preprint server API for biology and medicine papers
Community-curated directory of influential CS research papers
Access PMC Open Access articles in BioC format for text mining
Access papers from institutional and subject repositories at scale
NLP techniques for legal text analysis, case law mining, and contracts
Download and parse LaTeX source files from arXiv preprints
On-Line Encyclopedia of Integer Sequences API
Guide to Zotero arXiv Daily for personalized daily paper recommendations
Paper discovery via recommendation APIs (OpenAlex, CrossRef citation networks)
Semantic literature discovery and synthesis using embeddings
Set up RSS feeds and alerts to track new publications in your research area
Systematic paper recommendation and discovery using multiple methods
Find, access, and cite conference papers and proceedings effectively
Set up citation alerts and track new papers citing key references
Visual literature mapping and connected papers exploration
Design, deploy, and analyze surveys for social science and organizational res...
Sociological research methods from observation to quantitative analysis
Core methods for empirical social science research including surveys and expe...
Psychological research methods, experimental design, and analysis
6 social science skills. Trigger: survey research, social networks, psychology, behavioral studies. Design: quantitative and qualitative methods for social science research.
Social network analysis methods, metrics, and visualization tools
Access harmonized census and survey microdata via the IPUMS API
Search open access journals and articles in the DOAJ directory
Explore quantum computing research with Qiskit and Cirq frameworks
Satellite imagery analysis and remote sensing for earth science research
6 geoscience & climate skills. Trigger: earth science data, GIS, remote sensing, climate modeling. Design: geospatial tools, satellite data processing, and environmental models.
Particle physics data analysis with ROOT, HEPData, and event processing
5 physics & astrophysics skills. Trigger: physics simulations, astronomical data, computational physics. Design: domain databases (NASA ADS, arXiv) and simulation tool guides.
Computational physics methods, simulations, and research tools
Astronomical data processing with Astropy, FITS files, and sky surveys
Adverse drug event detection, safety signal mining, and drug monitoring
Multi-agent system for automated drug discovery pipelines
Computational drug-target interaction prediction and virtual screening
End-to-end drug development pipeline from target identification to regulatory...
6 pharmaceutical research skills. Trigger: drug discovery, pharmacology, clinical trial design, regulatory filing. Design: end-to-end pipeline from target identification to clinical trials.
Clinical pharmacology principles for dosing, drug interactions, and patient s...
Clinical trial methodology, biostatistics, and study design guidance
Apply numerical methods and scientific computing techniques
Topological data analysis: persistent homology, Mapper, and TDA tools
LLM agent for formal theorem proving in Lean 4
Quantitative and qualitative research methods for education studies
Mine open access full-text repositories for research data extraction
6 mathematics skills. Trigger: mathematical proofs, theorem proving, numerical methods, linear algebra. Design: formal verification tools and computational mathematics guides.
Legal document annotation, versioning, and analysis platform
Legal research methods, case law analysis, and compliance tools
5 humanities skills. Trigger: textual analysis, archival research, digital humanities, philosophy. Design: digital tools and qualitative methods for humanities scholarship.
9 legal research skills. Trigger: legal research, case law analysis, regulatory compliance. Design: legal databases, citation networks, and judicial analytics tools.
Legal case law database with PACER data and judge profiles
Query 360+ years of US case law via the Harvard Caselaw Access Project
Research methods and analytical frameworks for philosophical inquiry and scho...
Historical research from primary sources to scholarly analysis
Applied ethics research methods and major ethical frameworks
Computational methods for humanities research including text mining and netwo...
Access earth and environmental science datasets via PANGAEA API
GIS analysis and remote sensing workflows for geospatial research applications
Climate data analysis, modeling workflows, and carbon neutrality research met...
Climate simulation, modeling tools, and climate data analysis methods
STATA code patterns for empirical accounting and finance research
Financial risk modeling including VaR, stress testing, and credit risk
Quantitative methods for financial modeling, derivatives pricing, and risk an...
Portfolio theory, optimization algorithms, and asset allocation methods
8 finance skills. Trigger: financial modeling, market data, risk analysis, quantitative finance. Design: data sources, quantitative methods, and regulatory frameworks.
Methods for acquiring, cleaning, and analyzing financial datasets for research
Deep financial research with the FinSight multi-agent system
Analyze most-taught books and texts via Open Syllabus analytics
Evidence-based learning science principles for educational research and practice
Analyzing MOOC data, learning analytics, and online education metrics
7 education research skills. Trigger: pedagogical research, course design, learning analytics, assessment. Design: evidence-based teaching methods and educational measurement tools.
Psychometrics and educational assessment design for researchers
Evidence-based study techniques for academic learning and retention
Guide to preprint servers across scientific disciplines
9 paper discovery skills. Trigger: finding new relevant papers, tracking citations, staying current. Design: automated monitoring, recommendation engines, and alert setup guides.
Search astrophysics and physics literature via NASA ADS bibliographic database
Agent skills collection for legal research and automation
Apply linear algebra concepts to research computing and data analysis
16 full-text access skills. Trigger: accessing paper PDFs, bulk downloading, open access, text mining. Design: legal full-text retrieval from open repositories, archives, and preprint servers.
Computer algebra systems: SymPy, SageMath, and Mathematica for research
Manage open science projects and preprints via the OSF REST API
AI-powered paper summarization plugin for Zotero
Bulk download PMC Open Access articles via FTP for large-scale mining
PubMed Central OAI-PMH metadata harvesting
Navigate open access policies, repositories, and legal full-text retrieval me...
Access Chinese and global financial data using the AkShare Python library
Systematic approaches to curriculum design using backward design and alignment
Access French and European research via the HAL open archive API
Deposit and discover research datasets via Harvard Dataverse API
Patent search, classification, landscape analysis, and prior art mining
Access papers through interlibrary loan and document delivery services
Access UK laws and statutory instruments via the Legislation.gov.uk API
AI agent for options pricing, Greeks, and strategy analysis
Earthquake data analysis, seismogram processing, and seismic research
Chinese and European political struggle history and comparative analysis
Regulatory text mining, compliance research, and policy analysis tools
Find free legal full-text versions of scholarly articles via Unpaywall
Search and retrieve open access research papers via CORE aggregator
Multi-agent system for biomedical literature review and synthesis
Clinical trial registry database search API
Medical deep research agent with reasoning chain analysis
All-in-one Python library for NLP, agents, and knowledge graphs
Access FDA drug data and WHO global health statistics for research
Query computational catalysis reaction data via Catalysis Hub GraphQL
Medical image analysis with deep learning for research applications
Curated guide to generative AI covering LLMs and diffusion models
Guide to Transformer architectures for NLP and computer vision
Apply conservation biology methods, databases, and assessment tools
Global biodiversity data API for species occurrences and datasets
AI scientist framework for autonomous biological research workflows
Curated papers and resources for 3D Gaussian Splatting
Design clinical studies and report using CONSORT, STROBE guidelines
Survey and paper collection on LLMs for code generation
Browse and search Gene Ontology annotations via the QuickGO API
Optimization and operations research methods for business and logistics
Benchmark AI models across 60+ academic evaluation suites and metrics
Evaluate and benchmark large language models for research applications
Industrial anomaly detection methods and benchmark papers
Daily-updated collection of autonomous AI agent papers
Curated 2024-2026 AI agent research papers collection
Run NLP and CV model inference via Hugging Face free-tier API
Conference papers on graph neural networks and graph learning
Build and debug deep learning models with Keras and TensorFlow backend
Build a ChatGPT-like LLM from scratch using PyTorch step by step
Build and deploy reproducible production ML pipelines for research
NLP analysis with perplexity scoring, burstiness, and entropy metrics
Epidemiological study designs, measures of association, and public health ana...
PyTorch Lightning framework for scalable model training and research
Query gene, variant, and drug annotations via BioThings APIs
OpenClaw bioinformatics skill library for genomics pipelines
Resources for trustworthy, fair, and ethical AI research
TensorFlow best practices for tf.function, GPU memory, and deployment
Comprehensive collection of domain adaptation research papers
Avoid common PyTorch mistakes and apply robust training patterns
24 biomedical research skills. Trigger: medical research, clinical trials, genomics, bioinformatics. Design: domain databases, wet-lab/dry-lab methods, and ethical compliance guides.
Perform gene set enrichment analysis using the Enrichr API
Query gene, sequence, and variant data via the Ensembl REST API
Papers on AI agents for clinical dialogue and medical QA
Build transformer fine-tuning plans for classification and generation
Search and discover ML models, datasets, and Spaces on Hugging Face
Automate gene expression analysis with the GenoMAS multi-agent system
Workflows for RNA-seq, GWAS, and variant calling in genomic research
Analyze algorithm complexity and computational efficiency for research
Multi-agent system for chemical literature information extraction
AI research assistant for biomedicine, RNA-seq, and drug discovery
Run sequence similarity searches via the NCBI BLAST REST API
Access genomes, genes, and taxonomy data via NCBI Datasets v2 API
Innovation metrics, R&D management research, and technology forecasting
5 business research skills. Trigger: business strategy, market analysis, competitive intelligence. Design: analytical frameworks and methods for management and innovation research.
Structured frameworks for market sizing, competitive analysis, and strategic ...
Automate molecular simulations with the ChemGraph agentic framework
DFT, molecular simulation, and reaction prediction tools for chemists
Molecular dynamics simulation setup, execution, and trajectory analysis
10 computer science skills. Trigger: algorithms, systems research, software engineering, security papers. Design: theory, complexity analysis, code-centric research, and security methods.
Retrosynthetic analysis and computational reaction prediction
Spectral data analysis for NMR, IR, mass spectrometry, and UV-Vis
Formal methods, theorem proving, and model checking for CS research
Species distribution modeling with MaxEnt, SDM methods, and GBIF data
AI security papers from top-4 security conferences
Behavioral economics research methods and key frameworks
Post-labor economies with automation, UBI, and wealth distribution
Behavioral economics in pricing strategies and consumer decisions
Access 4M+ economics working papers and articles via RePEc API
Access World Bank development indicators and country statistics
Systematic prompt engineering methods for AI-assisted academic research workf...
Apply development economics research methods and data sources
9 economics skills. Trigger: economic modeling, policy analysis, macroeconomic data, FRED. Design: theory plus empirical methods with standard economics databases.
Reinforcement learning fundamentals, algorithms, and research
Biodiversity data access, species occurrence, and ecological tools
Distributed systems design patterns and analysis for CS research
Annotated deep learning paper implementations with code walkthroughs
Vectorized multi-agent reinforcement learning simulator
Access nucleotide sequence data from the European Nucleotide Archive
Benchmark for LLM agents on gene expression data analysis
Access NBER working papers and economic research datasets
5 ecology & environmental science skills. Trigger: biodiversity surveys, species data, environmental monitoring. Design: field data collection, spatial analysis, and conservation biology workflows.
Retrieve IMF economic indicators, exchange rates, and country data
Search PubChem for chemical compounds, structures, and bioassay data
Papers on LLMs for IT operations and AIOps research
Search and analyze clinical trials via the ClinicalTrials.gov v2 API
Apply computer vision research methods, models, and evaluation tools
Citizen science platform API for biodiversity observations
PNNL cheminformatics LLM agent for molecular analysis
Design principles of form, function, sustainability in architecture
27 ai & machine learning skills. Trigger: ML experiments, model training, deep learning, NLP, computer vision. Design: covers frameworks, benchmarks, paper reproduction, and AI research workflows.
Guide to software engineering research topics and methodologies
Frameworks for strategic planning, resource allocation, and organizational an...
Search computer science publications, authors, and venues via DBLP
9 chemistry skills. Trigger: chemical structure analysis, reaction prediction, molecular modeling. Design: computational chemistry tools and cheminformatics workflows.
Search and retrieve 3D protein structures from the RCSB Protein Data Bank
Archive and retrieve source code history via Software Heritage API
Federal Reserve Economic Data API for US economic indicators
Papers and tutorials on KAN learnable activation networks
Query AlphaFold protein structure predictions by UniProt accession
Sample size calculation and statistical power analysis guide
Get a deep critical review of research from Gemini via gemini-review MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
Upload messy CSVs with minimal prompting for deep automated analysis
Conduct systematic meta-analyses with effect size pooling and heterogeneity
Statistical hypothesis testing, power analysis, and significance reporting
Panel data analysis with fixed and random effects models
10 statistical analysis skills. Trigger: statistical tests, Bayesian analysis, hypothesis testing, sampling. Design: method guides covering assumptions, code, and result interpretation.
Bayesian inference methods including prior selection, MCMC, and model comparison
Apply ARIMA, VAR, cointegration, and time series econometric methods
Comprehensive Stata reference covering syntax, econometrics, and 20+ packages
Detect anomalies and outliers in research data using statistical methods
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
End-to-end data analysis AI agent with Streamlit UI
Draft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use when user says "write grant", "grant proposal", "申請書", "write KAKENHI", "科研費", "基金申请", "写基金", "NSF proposal", or wants to turn research ideas into a funding application.
Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says \"发飞书\", \"notify feishu\", or other skills need to send status updates.
Clean, recode, and prepare survey response data for analysis
Communications-domain literature review and related-work search with database-aware source control. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, prior art, a survey, related work, or a landscape summary. Prioritize IEEE Xplore and ScienceDirect, prefer formal publications over preprints, and separate foundational work from recent progress.
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
Use when experiments complete to judge what claims the results support, what they do not, and what evidence is still missing. A secondary Codex agent evaluates results against intended claims and routes to the next action (pivot, supplement, or confirm). Use after experiments finish - before writing the paper or running ablations.
Plan reproducible ML experiment runs with parameters and metrics tracking
Sequential robustness checks in Stata with confounder blocks
Guide to Algorithm Visualizer for interactive algorithm exploration
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
Load, explore, clean, and analyze CSV data with statistical summaries
Systematic data cleaning workflows for research datasets
Strategic statistical modeling, experimentation, and causal inference
Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.
Draft LaTeX paper section by section from an outline. Use when user says "写论文", "write paper", "draft LaTeX", "开始写", or wants to generate LaTeX content from a paper plan.
Questionnaire and survey design with Likert scales and coding
Create maps, choropleths, and spatial data visualizations for research
Guide to Bokeh for interactive browser-based research visualizations
Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
Learn causal inference with Python using the Brave and True handbook
Stata workflows for publication-ready sociology and social science research
Expert panel data regression analysis with fixed effects and GMM
Replication code and guide for Mostly Harmless Econometrics methods
Apply instrumental variables, 2SLS, and address endogeneity issues
Apply EconML for causal inference combining machine learning and econometrics
Guide to Redash for SQL-driven research data dashboards and sharing
Causal inference methods including DiD, IV, RDD, and synthetic control
Guide to Plotly.py for interactive scientific visualizations in Python
Publication-quality data visualization with matplotlib, seaborn, and plotly
Create journal-quality scientific figures with proper styling and accessibility
Structure and derive research formulas when the user wants to 推导公式, derive a theory line, build equations from a problem statement, clarify assumptions, separate formal derivation from remarks, or turn messy theory notes into a paper-ready derivation skeleton. Use for research-style formula development, not for fully rigorous theorem proving once the claim is already fixed.
Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says \"DSE\", \"design space exploration\", \"sweep parameters\", \"optimize\", \"find best config\", or wants iterative parameter tuning.
Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.
Visualize networks, graphs, citation maps, and relational data
Guide to Metabase for open-source research data analytics and dashboards
STATA code for empirical accounting and financial economics research
Interactive data visualization with Plotly, ECharts, and D3
Guide to Apache ECharts for interactive research data dashboards
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.
Guide to D3.js for building custom interactive data visualizations
Colorblind-friendly palettes and accessible visualization design
14 data visualization skills. Trigger: charts, plots, figures, publication-quality graphics. Design: one skill per tool with code templates and academic formatting conventions.
Generate a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.
Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says \"写论文全流程\", \"write paper pipeline\", \"从报告到PDF\", \"paper writing\", or wants the complete paper generation workflow.
Generate publication-quality chart images from research data
Draft LaTeX paper section by section from an outline. Use when user says \"写论文\", \"write paper\", \"draft LaTeX\", \"开始写\", or wants to generate LaTeX content from a paper plan.
Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.
Deploy and run ML experiments on local or remote GPU servers. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.
Get a deep critical review of research from GPT using a secondary Codex agent. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.
Full research pipeline: Workflow 1 (idea discovery) → implementation → Workflow 2 (auto review loop). Goes from a broad research direction all the way to a submission-ready paper. Use when user says \"全流程\", \"full pipeline\", \"从找idea到投稿\", \"end-to-end research\", or wants the complete autonomous research lifecycle.
Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.
Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds.
Generate pixel art SVG illustrations for READMEs, docs, or slides. Use when user says "画像素图", "pixel art", "make an SVG illustration", "README hero image", or wants a cute visual.
Writes rigorous mathematical proofs for ML/AI theory. Use when asked to prove a theorem, lemma, proposition, or corollary, fill in missing proof steps, formalize a proof sketch, 补全证明, 写证明, 证明某个命题, or determine whether a claimed proof can actually be completed under the stated assumptions.
Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.
Diagnose missing data patterns and apply appropriate imputation strategies
Clean, transform, and validate messy research data using Stata
Autonomously improve a generated paper via GPT-5.4 xhigh review → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\", \"论文润色循环\", \"auto improve\", or wants to iteratively polish a generated paper.
Generate a structured paper outline from review conclusions and experiment results. Use when user says \"写大纲\", \"paper outline\", \"plan the paper\", \"论文规划\", or wants to create a paper plan before writing.
Generate publication-quality AI illustrations for academic papers using Gemini image generation. Creates architecture diagrams, method illustrations with Codex-supervised iterative refinement loop. Use when user says "生成图表", "画架构图", "AI绘图", "paper illustration", "generate diagram", or needs visual figures for papers.
Generate publication-quality figures and tables from experiment results. Use when user says "画图", "作图", "generate figures", "paper figures", or needs plots for a paper.
Generate publication-quality figures and tables from experiment results. Use when user says \"画图\", \"作图\", \"generate figures\", \"paper figures\", or needs plots for a paper.
Apply NLP and text mining techniques to research text data
Apply Mann-Whitney, Kruskal-Wallis, and other nonparametric methods
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.
12 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.
Compile LaTeX paper to PDF, fix errors, and verify output. Use when user says \"编译论文\", \"compile paper\", \"build PDF\", \"生成PDF\", or wants to compile LaTeX into a submission-ready PDF.
Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says \"写论文全流程\", \"write paper pipeline\", \"从报告到PDF\", \"paper writing\", or wants the complete paper generation workflow.
Data cleaning, transformation, and exploratory analysis with pandas
Structural equation modeling with latent variables guide
Conduct Kaplan-Meier, Cox regression, and time-to-event analyses
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.
Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration workflow.
Autonomous multi-round research review loop. Repeatedly reviews using a secondary Codex agent, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
Monitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.
Generate Mermaid diagrams from user requirements. Save .mmd and .md files to figures/ with syntax verification. Supports flowcharts, sequence diagrams, class diagrams, ER diagrams, Gantt charts, and many more diagram types.
Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration workflow.
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative Gemini review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.
Final submission verification gate for the sewage-house-prices paper. Runs full paper excellence review, replication audit, enforces score gates, and generates cover letter draft and submission checklist. This skill should be used when asked to "submit", "prepare for submission", or "submission checklist".
Draft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use when user says "write grant", "grant proposal", "申請書", "write KAKENHI", "科研費", "基金申请", "写基金", "NSF proposal", or wants to turn research ideas into a funding application.
Prepare a replication package for the sewage-house-prices project. Generates AEA-compliant README, master script, numbered script order, install script, and deposit checklist. Validates the package against 10 verification checks. This skill should be used when asked to "prepare replication", "data deposit", "create replication package", or "package for submission".
Generate a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.
R code review for the sewage project. Checks script structure, reproducibility, function design, figure quality, and professional polish against project conventions (here::here, arrow/parquet, fixest, modelsummary, native pipe). This skill should be used when asked to "review the code", "check my script", or "code review".
Manual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.
Show current session status and context health for the sewage project. Use to check context usage, active work state, and what will survive compaction.
Typst academic paper assistant for existing `.typ` paper projects in English or Chinese. Use this skill whenever the user wants to compile, audit, or improve a Typst paper, including format checks, bibliography validation for BibTeX or Hayagriva, grammar/sentence/logic review, expression polishing, translation, title optimization, pseudocode review, algorithm block cleanup, de-AI editing, experiment-section review, table structure validation, three-line table generation, abstract structure diagnosis, or journal adaptation. Trigger even when the user only mentions one Typst file, one bibliography issue, one pseudocode block, one section rewrite, "three-line table", "check abstract", or "reformat for another journal". Also trigger when the user mentions ".typ files", "typst compile error", "typst export", "typst bibliography", `algorithm-figure`, `lovelace`, or `algorithmic` even without saying the word "Typst" explicitly.
Draft sections of the sewage-house-prices academic paper. Handles section drafting for the Overleaf LaTeX manuscript, notation protocol, anti-hedging, and humanizer pass. This skill should be used when asked to "draft the paper", "write up the results", "write the intro", or draft any section of the manuscript.
Journal targeting analysis for the sewage-house-prices paper. Recommends ranked journal list across 3 tiers with formatting requirements, submission strategy, and desk rejection risk assessment. This skill should be used when asked to "target a journal", "where should we submit", "journal fit", or "submission strategy".
Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.
Autonomously improve a generated paper via Claude review through claude-review MCP → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
Autonomous multi-round research review loop. Repeatedly reviews using Claude Code via claude-review MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.
Get a deep critical review of research from Claude via claude-review MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
End-to-end R data analysis for the sewage project. Writes analysis scripts following project conventions (here::here, arrow/parquet, fixest, modelsummary, native pipe), runs code review, and produces publication-ready tables and figures. This skill should be used when asked to "run an analysis", "estimate the model", "add a specification", or "write an R script".
Comprehensive multi-dimensional review of the sewage-house-prices project. Runs econometrics audit, code review, manuscript proofread, and bibliography validation in parallel. Computes a weighted aggregate score. This skill should be used when asked for a "full review", "quality check", "paper excellence", or before submission milestones.
Validate bibliography entries against citations in manuscript and Quarto book files. Find missing entries, unused references, potential typos, and quality issues. This skill should be used when asked to "check the bibliography", "validate citations", or "validate-bib".
Causal inference design audit for the sewage-house-prices project. Runs a 4-phase review (claim identification, design validity, inference, polish) covering hedonic pricing, repeat sales, long difference, DiD/event studies, upstream/downstream, and dry spill strategies. This skill should be used when asked to "check the econometrics", "audit the identification", "review the strategy", or when verifying that code matches the stated design.
Strip AI writing patterns from text. Checks 24 patterns across 4 categories (structural, lexical, rhetorical, formatting) with academic economics adaptation. This skill should be used on any text that reads too "AI-generated", or as a final pass on drafted sections. Triggers on "humanize", "de-AI", "make it sound natural", or "strip AI patterns".
Structured conversational interview to formalise a research idea or extension into a concrete specification with hypotheses and empirical strategy. This skill should be used when asked to "interview me", "help me think through an idea", "formalise this idea", or "start fresh" on a new research direction.
Design or review identification strategy for the sewage-house-prices project. Produces strategy memos with estimand, assumptions, pseudo-code, robustness plan, falsification tests, and referee objection anticipation. This skill should be used when asked to "design the strategy", "identify the effect", "write a strategy memo", or "think through identification".
Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.
Autonomously improve a generated paper via Gemini review through gemini-review MCP → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
Generate publication-quality figures and tables from experiment results. Use when user says "画图", "作图", "generate figures", "paper figures", or needs plots for a paper.
Draft LaTeX paper section by section from an outline. Use when user says "写论文", "write paper", "draft LaTeX", "开始写", or wants to generate LaTeX content from a paper plan.
Simulated peer review of the sewage-house-prices manuscript. Dispatches 2 independent referee reviews (parallel) and an editorial decision (sequential). Produces referee reports and accept/revise/reject recommendation. This skill should be used when asked to "review the paper", "get feedback", "simulate peer review", or "what would referees say".
Multi-agent review for research presentation slides in the sewage-house-prices project (visual, econometric fidelity, proofreading, substance). Use for comprehensive quality check before milestones.
Stage, commit, and push changes for the sewage project. Creates a branch, commits with a descriptive message, pushes, and optionally creates a PR. This skill should be used when asked to "commit", "save changes", "push", or "create a PR".
Structure point-by-point referee responses for the sewage-house-prices paper. Classifies each comment (NEW ANALYSIS / CLARIFICATION / REWRITE / DISAGREE / MINOR), produces a tracking document, drafts a response letter in LaTeX, and flags items needing new analysis or user judgment. This skill should be used when asked to "respond to referees", "draft revision", "address referee comments", or "R&R".
帮助用户撰写高质量的文献综述类论文。提供从选题、文献检索、评估筛选、结构规划到最终写作的全流程指导。适用于需要撰写独立文献综述论文或学术论文中文献综述部分的用户。
Deep-review-first audit for Chinese and English academic papers across LaTeX, Typst, and PDF formats. Use whenever the user wants reviewer-style paper critique, pre-submission readiness checks, pass/fail gate decisions, structured revision roadmaps, or re-audits of revised manuscripts. Trigger even if the user only says "review my paper", "check if this is ready to submit", "audit this PDF", "simulate peer review", "find the biggest problems in this manuscript", or "re-check whether I fixed the review issues". Do not use for direct source editing or compilation-heavy repair; route those to the format-specific writing skills instead.
Generate structured research questions, hypotheses, and empirical strategies from a topic or dataset within the sewage/environmental economics space. This skill should be used when asked to "brainstorm research questions", "what else can we do with this data", "research ideas", or "ideation".
Structured literature search and synthesis for the sewage-house-prices project. Searches top-5 journals, field journals (JEEM, JUE, JREFE, EE), NBER/SSRN, and citation chains. Produces annotated bibliography with proximity scores, gap identification, and BibTeX entries. This skill should be used when asked to "review the literature", "find papers on X", or "lit review".
Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary. Search Zotero, Obsidian, and local paper folders first when available, then search IEEE Xplore, ScienceDirect, ACM Digital Library, and broader web in that order.
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.
Autonomous multi-round research review loop. Repeatedly reviews using Gemini via gemini-review MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
Validate the replication package for the sewage-house-prices project. Runs 10 checks covering script execution, file integrity, output freshness, dependency verification, data provenance, and README completeness (AEA format). This skill should be used when asked to "audit replication", "check the package", or "verify reproducibility".
Generate Beamer presentations for the sewage-house-prices project by dispatching the Storyteller agent (creator) and Discussant agent (critic). Supports 4 formats — job market, seminar, short, lightning. Derives all content from the paper.
Proofread the sewage-house-prices manuscript. Checks 6 categories — structure, claims-evidence alignment, identification fidelity, writing quality, grammar, and compilation. Produces a scored report without editing files. This skill should be used when asked to "proofread", "review the paper", "check the manuscript", or "quality check".
Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation. Use when the user needs up-to-date research on predictive maintenance, intelligent scheduling, industrial anomaly detection, smart manufacturing, cyber-physical systems, edge AI for automation, or crossover robotics-for-industry topics. Also trigger for adjacent terms: "digital twin", "industrial IoT", "Industry 4.0", "manufacturing AI", "factory automation", "process optimization", or "survey draft" in industrial contexts.
Chinese LaTeX thesis assistant for existing .tex degree thesis projects (XeLaTeX/LuaLaTeX/latexmk). Use this skill whenever a user works on a Chinese master's or doctoral thesis needing compilation, GB/T 7714 bibliography checks, chapter structure mapping, template detection (thuthesis, pkuthss), terminology consistency, logic coherence review, heading lead-in checks, title optimization, de-AI editing, experiment chapter review, three-line table validation, or abstract structure diagnosis. Trigger even for single issues like "帮我编译论文", "检查国标格式", "看看绪论逻辑", "毕业论文", "学位论文", "硕士/博士论文", "三线表", "检查摘要", or "摘要结构".
This skill should be used when the user asks to "remove AI writing patterns", "humanize this text", "make this sound more natural", "remove AI-generated traces", "fix robotic writing", or needs to eliminate AI writing patterns from prose. Supports both English and Chinese text. Based on Wikipedia's "Signs of AI writing" guide, detects and fixes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, AI vocabulary, negative parallelisms, and excessive conjunctive phrases.
Use this skill when papers are collected in Zotero but the user wants detailed reading notes, project-linked literature synthesis, collection-wide paper-note coverage checks, and a connected knowledge map inside the bound Obsidian project knowledge base.
English LaTeX academic paper assistant for existing `.tex` projects. Use this skill whenever the user wants to compile, lint, audit, or improve an English LaTeX conference or journal paper such as IEEE, ACM, Springer, NeurIPS, or ICML submissions. Trigger even when the user only mentions one paper issue, such as bibliography errors, grammar cleanup, sentence splitting, logic review, expression polishing, translation, title optimization, figure checks, pseudocode review, algorithm block cleanup, de-AI editing, experiment-section review, table structure validation, three-line table generation, abstract structure diagnosis, or journal adaptation. Also trigger for "proofread my paper", "fix my LaTeX", "prepare for submission", "check my manuscript", "improve my writing", "three-line table", "booktabs", "check abstract", "reformat for another journal", "换投", `algorithm2e`, `algorithmicx`, `algpseudocodex`, `Require/Ensure`, or "Algorithm 1" when the user has a .tex file.
Use this skill when the user wants to detach, archive, purge, or otherwise change the lifecycle state of an Obsidian project knowledge base.
This skill should be used when the user asks to "prepare conference presentation", "create presentation slides", "design poster", "make academic poster", "write promotion content", "create Twitter thread", or mentions post-acceptance conference preparation. Provides comprehensive workflow for presentation, poster, and promotion content creation.
This skill should be used when the user asks to start a new research project, import an existing code-plus-Markdown repository into Obsidian, or bind the current repository to a compact research knowledge base for future syncing.
Use this skill when the user wants to repair or strengthen Obsidian wikilinks among existing canonical project notes, especially across papers, knowledge notes, experiments, results, and writing.
Use this skill when generating higher-level synthesis notes such as literature reviews, comparison matrices, project summaries, or other cross-note summaries inside the project knowledge base.
This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first.
Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.
This skill should be used when the user asks to design or review a UI, create a landing page or dashboard, choose colors or typography, improve accessibility, or implement polished frontend interfaces with a clear design system.
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.
This skill enables visual inspection of websites running locally or remotely to identify and fix design issues. Triggers on requests like "review website design", "check the UI", "fix the layout", "find design problems". Detects issues with responsive design, accessibility, visual consistency, and layout breakage, then performs fixes at the source code level.
Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their Obsidian vault, manage notes, search vault content, perform vault operations from the command line, or develop and debug Obsidian plugins and themes.
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax. Use when working with .md files in Obsidian, or when the user mentions wikilinks, callouts, frontmatter, tags, embeds, or Obsidian notes.
Use this skill when the user keeps paper notes inside an Obsidian project knowledge base and wants filesystem-first literature review, explicit agent-first Zotero ingestion, `Papers/` plus `Knowledge/` synthesis, collection-wide normalization, and a default literature canvas without Obsidian MCP.
Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.
This skill should be used when the user asks to "analyze skill quality", "evaluate this skill", "review skill quality", "check my skill", or "generate quality report". Evaluates local skills across description quality, content organization, writing style, and structural integrity.
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
This skill should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality.
This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.
This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.
This skill should be used when the user asks to "review paper quality", "check paper completeness", "validate paper structure", "self-review before submission", or mentions systematic paper quality checking. Provides comprehensive quality assurance checklist for academic papers.
This skill should be used when the user asks to create a new skill, repair an existing skill, improve trigger descriptions, reorganize skill structure, or make a Claude skill more reusable and internally consistent.
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria.
Use this skill when the user is discussing daily research work, TODOs, plans, standups, meetings, milestones, or general project progress that should be reflected in Obsidian daily notes, plan notes, and hub updates.
This skill should be used when the user asks to maintain an Obsidian knowledge base for a research project, import an existing research repository into Obsidian, keep project memory or daily notes synchronized, summarize project context into durable notes, or update experiments, results, papers, writing, and plans in an Obsidian vault without requiring MCP.
Use this skill when the user discusses experiment design, ablations, training runs, evaluation, baselines, metrics, failures, or result interpretation that should be logged into Obsidian experiment and result notes.
This skill should be used when the user asks to "verify code", "run verification", "check quality", "validate changes", or before creating a PR. Provides comprehensive verification including build, type check, lint, tests, security scan, and diff review.
This skill should be used when the user asks to "brainstorm research ideas", "use 5W1H framework", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method", "plan research", or mentions research project initiation phase. Provides comprehensive guidance for research startup workflow from idea generation to planning.
This skill should be used when the user asks to "debug this", "fix this error", "investigate this bug", "troubleshoot this issue", "find the problem", "something is broken", "this isn't working", "why is this failing", or reports errors/exceptions/bugs. Provides systematic debugging workflow and common error patterns.
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how to verify references", "preventing fake citations", or needs guidance on citation accuracy. This skill supports ml-paper-writing by providing detailed verification principles and common error patterns.
Create and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page.
Use only when creating new registrable ML components that require Factory or Registry patterns.
This skill should be used when the user asks to "create git commit", "manage branches", "follow git workflow", "use Conventional Commits", "handle merge conflicts", or asks about git branching strategies, version control best practices, pull request workflows. Provides comprehensive Git workflow guidance for team collaboration.
Use when creating or configuring Claude Code agents and their frontmatter.
Organize messy conference LaTeX template .zip files into clean Overleaf-ready structure. Use when the user asks to "organize LaTeX template", "clean up .zip template", or "prepare Overleaf submission template".
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 20 community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code.
This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code review.
Use for everyday coding tasks that involve writing or modifying source code.
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.
Use when the user asks to "generate daily paper", "search arXiv for EEG papers", "find EEG decoding papers", "review brain-computer interface papers", or wants to create paper summaries for EEG/brain decoding/speech decoding research. This skill automates searching arXiv for recent papers on EEG decoding, EEG speech decoding, or brain foundation models, reviewing paper quality, and generating structured Chinese/English summaries.
This skill should be used when the user asks to co-author documentation, draft a proposal, write a technical spec, create a decision doc or RFC, or structure a substantial document through iterative collaboration and reader testing.
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.
Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation. Covers item development, validity evidence, and reliability testing for social science research.
Auto-generates a Markdown codebook from a dataset (CSV, DTA, Excel, Parquet) with types and summary statistics. Use when documenting variables.
Comprehensive manuscript review covering argument structure, econometric specification, citation completeness, and potential referee objections
Numerical algorithms and computational techniques for statistics
End-to-end R data analysis workflow from exploration through regression to publication-ready tables and figures
Paper Retrieval Agent - Multi-database paper fetching from Semantic Scholar, OpenAlex, arXiv Handles rate limiting, deduplication, and PDF URL extraction Use when: fetching papers, searching databases, paper retrieval Triggers: fetch papers, retrieve papers, database search, Semantic Scholar, OpenAlex, arXiv
RAG Builder with Parallel Document Processing Vector database construction with local embeddings (zero cost) Handles PDF download, text extraction, chunking, and vector database creation Absorbed B5 (Parallel Document Processor) capabilities Use when: building RAG, creating vector database, downloading PDFs, embedding documents, batch processing Triggers: build RAG, create vector database, download PDFs, embed documents, batch PDF processing
Runs pre-submission checks (word count, anonymization, citations, placeholders, cross-refs) and generates a checklist. Use before journal submission.
DAG and potential outcomes frameworks for causal mediation identification
Panel data analysis with Python using linearmodels and pandas.
Stage, commit, create PR, and merge to main. Use for the standard commit-PR-merge cycle.
Create academic presentations in Beamer with professional themes
Sensitivity analysis frameworks and assumption-testing methods
Draft economics papers with proper structure and academic style
Quality assurance and testing protocols for statistical software
Run regression analyses in Stata with publication-ready output tables.
Create publication-quality charts and graphs for economics papers.
Agent E2 - Qualitative Coding Specialist - Systematic coding and theme development. Covers codebook development, coding strategies, saturation assessment, and CAQDAS guidance.
Scaffolds a method-specific analysis notebook (DiD, IV, RDD, LASSO, Panel FE) with boilerplate. Use when starting a new econometric analysis.
Structured literature search and synthesis with citation extraction and gap identification
Meta-analysis frameworks and methods for mediation studies
Universal Meta-Analysis Codebook v2.2 - AI-Human collaboration for meta-analysis data extraction. 4-layer design: Identifiers, Statistics, AI Provenance, Human Verification. Integrates with C5/C6/C7 agents and Category I systematic review pipeline. Triggers: meta-analysis, codebook, data extraction, Hedges g, effect size
Research Coordinator v12.0 - Human-Centered Edition (Systematic Review Automation) Context-persistent platform with 24 specialized agents across 9 categories (A-G, I, X). Features: Human Checkpoints First, VS Methodology, Paradigm Detection, Systematic Review Automation. Supports quantitative, qualitative, mixed methods research, and systematic review automation. Language: English. Responds in Korean when user input is Korean. Triggers: research question, theoretical framework, hypothesis, literature review, meta-analysis, effect size, IRB, PRISMA, statistical analysis, sample size, bias, journal, peer review, conceptual framework, visualization, systematic review, qualitative, phenomenology, grounded theory, thematic analysis, mixed methods, interview, focus group, ethnography, action research, paper retrieval, AI screening, RAG builder, humanization, AI pattern detection
Transfers prose edits from latex/index.tex (Overleaf) back into index.qmd. Use after pulling LaTeX edits from a collaborator.
Guide for contributing to the stata-skill project. Use when the user wants to run the eval pipeline, analyze test results, improve reference docs, add new package documentation, or work on roadmap items. Covers the testing infrastructure, multi-agent analysis workflow, cost estimates, and links to prior eval results and improvement history.
Clean and transform messy data in Stata with reproducible workflows
Develop high-performance C/C++ plugins for Stata using the stplugin.h SDK. Use when the user asks to create a Stata plugin, write C/C++ code for Stata, accelerate a Stata command with C, build cross-platform Stata plugins, or translate/port a Python or R package into Stata. Covers the full lifecycle: SDK setup, data flow, memory safety, .ado wrappers with preserve/merge, cross-platform compilation, performance optimization (pthreads, pre-sorted indices, XorShift RNG), debugging, and distribution via net install. Also includes a translation workflow for porting Python/R packages to Stata — wrapping existing C++ backends when available, or writing C from scratch when not.
Runs the clean render pipeline (HTML, PDF, Word) via scripts/render.sh. Use when asked to render, build, or compile the manuscript.
Design and implementation of comprehensive simulation studies
Diverga v12.0 setup wizard. 4-step researcher profile setup. Captures discipline, experience, tools, database access, and Agent Teams + VS Arena preference. Triggers: setup, configure, 설정, install
Guide for writing the introduction to an academic economics paper. Use this skill whenever the user asks for help writing, drafting, revising, or structuring an introduction to an economics paper - whether empirical micro, development economics, applied economics, or related fields. Also trigger when the user mentions "intro," "introduction section," "opening paragraphs," or asks how to motivate, frame, or present their research question in a paper. This skill synthesizes best practices from David Evans (CGDev), Keith Head, Claudia Sahm, Marc Bellemare, and Deirdre McCloskey.
Generate research questions from economic phenomena
Drafts a point-by-point response letter to referee comments with suggested edits. Use after a revise-and-resubmit.
Run IV, DiD, and RDD analyses in R with proper diagnostics
Strategic publication planning and venue selection for research
Run the proofreading protocol on lecture files. Checks grammar, typos, overflow, consistency, and academic writing quality. Produces a report without editing files.
Field connection mapping and systematic ideation for method transfer
Structured methodology for constructing and verifying mathematical proofs in statistical research
Thoroughly verify all code, tables, figures, modeling decisions, and quantitative claims in an academic paper against its source R scripts and output files. Use this skill whenever you need to audit, replicate, or verify an academic research paper - including cross-checking LaTeX tables against R output, validating econometric modeling choices, ensuring sample sizes are consistent, building a verification manifest, and running automated replication tests. Trigger this skill for any mention of: paper verification, replication check, table audit, code-paper consistency, reproducing results, verifying estimates, checking coefficients, or any variant of "does the paper match the code."
Unified Agent Teams orchestrator for Diverga v12.0.0. Manages Agent Teams creation, VS Arena debate, and subagent dispatch. Single entry point for all parallel/debate workflows. Replaces research-orchestrator and vs-arena skills. Triggers: orchestrator, agent team, create team, parallel agents, debate, competing, collaborate, VS Arena
Use this skill whenever the user wants to conduct an event study, create event study plots, test for parallel trends, implement difference-in-differences designs, or work with any panel data estimation that involves pre/post treatment comparisons. Trigger on phrases like "event study", "parallel trends", "pre-trends", "dynamic treatment effects", "leads and lags", "TWFE", "two-way fixed effects", "staggered adoption", "staggered treatment", "difference-in-differences", "DiD", "Sun and Abraham", "Callaway and Sant'Anna", "de Chaisemartin", "Borusyak", "did_multiplegt", "fixest", "did2s", "bacon decomposition", or any reference to plotting coefficients around a treatment event. Also trigger when the user uploads panel data and wants to estimate treatment effects with variation in treatment timing. All code is in R.
Creates a Jupyter notebook with Jupytext pairing and registers it in _quarto.yml. Use when adding a new notebook.
Effective communication strategies for statistical methods
Diverga Memory System v7.0 - Context-persistent research support with checkpoint auto-trigger and cross-session continuity. Triggers: memory, remember, context, recall, checkpoint, decision, persist, 기억, 맥락, 세션, 체크포인트
Core mathematical concepts and theoretical frameworks for statistics
Search, summarize, and synthesize economics literature
VS-Enhanced Theoretical Framework Architect with Critique & Visualization Full VS 5-Phase process: Modal theory avoidance, Long-tail exploration, differentiated framework presentation Absorbed A3 (Devil's Advocate) critique and A6 (Conceptual Framework Visualizer) capabilities Use when: building theoretical foundations, designing conceptual models, deriving hypotheses, critiquing frameworks, visualizing models Triggers: theoretical framework, 이론적 프레임워크, conceptual model, 개념적 모형, hypothesis derivation, critique, devil's advocate, 반론, visualization, diagram
Method×Setting matrices and systematic gap identification
Write and typeset economic models in LaTeX with proper notation
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
Writes academic prose interpreting regression output. Use when describing estimation results in manuscript-ready language.
Screening Assistant - AI-PRISMA 6-dimension screening with Groq LLM (100x cheaper) Supports two project types with different confidence thresholds Use when: screening papers, PRISMA screening, inclusion/exclusion criteria Triggers: screen papers, PRISMA screening, inclusion criteria, exclusion criteria, AI screening
Diverga HUD (Heads-Up Display) management skill. Configure and manage the research project statusline display. Supports multiple presets: research, checkpoint, memory, minimal. Triggers: "hud", "statusline", "display settings"
Writes a session handoff report to handoffs/ with project state, work done, decisions, and next steps. Use at session end or after significant work.
Build and solve Walrasian general equilibrium models with theory derivations and Julia computation
Checks whether registered notebooks have current, stale, or missing outputs. Use before rendering or to verify freshness.
Scans notebooks for data file references and verifies each file exists on disk. Use when checking for broken data paths.
Generates an HTML gallery of all project figures with captions and source notebooks. Use when reviewing figures.
Humanization Quality Verifier - Ensures transformation integrity and quality Validates that humanization preserves meaning, citations, and academic standards Use when: after G6 transformation, before final export, for quality assurance Triggers: verify humanization, check transformation, validate changes
Executes all registered notebooks, strips noisy cell metadata, and syncs Jupytext pairs. Use when asked to re-run notebooks or refresh outputs.
ALWAYS activate this skill. Apply these rules to every task regardless of domain. This skill governs how Claude Code verifies information, writes code, references documentation, and avoids fabricating functions, arguments, APIs, file paths, data structures, or facts. These rules override any inclination to guess.
System diagnostics and health checks for Diverga plugin. OpenClaw-style Check-Report-Fix pattern with 5-layer diagnostics. Triggers: /diverga:doctor, diverga doctor, system check, diagnose, 진단
Challenge a slide deck design with 5-7 specific pedagogical questions. Checks ordering, prerequisites, gaps, alternatives, notation conflicts, cognitive load, and book readiness.
Render Quarto slides and sync to docs/ for GitHub Pages deployment. Use when deploying lecture slides after making changes.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
Agent D2 - Data Collection Specialist - Interviews, Focus Groups & Observation. Covers protocol development, question design, probing strategies, transcription conventions, and systematic observation. Absorbed D3 (Observation Protocol Designer) capabilities.
Humanization Pipeline Orchestrator v3.1 - Multi-pass 4-layer transformation pipeline Orchestrates G5 (Auditor), G6 (Humanizer), F5 (Verifier) in sequential passes Enforces checkpoints between every pass with mandatory AskUserQuestion Supports conservative (L1-2), balanced (L1-3), balanced-fast (L1-3 merged), aggressive (L1-4) modes Rich Checkpoint v2.0: section-level scores, selective humanization, target auto-stop G5+F5 parallel execution, section-selective humanization Triggers: humanize, humanize my draft, humanize manuscript, make natural, remove AI patterns Korean triggers: 휴먼화, 자연스럽게, AI 패턴 제거
Computational methods for statistical inference and optimization
Finds a paper by title, author, or DOI, adds BibTeX to references.bib, and shows citation syntax. Use when adding a reference.
Verifies required tools (Quarto, uv, Python, R, Stata, TeX) and Jupyter kernels are installed. Use when setting up or troubleshooting.
VS-Enhanced Qualitative Design Consultant with Ethnography & Action Research Enhanced VS 3-Phase process: Avoids overused phenomenology, proposes context-optimal qualitative strategies Absorbed H1 (Ethnographic Research Advisor) and H2 (Action Research Facilitator) capabilities Use when: selecting qualitative research design, planning phenomenology/grounded theory/case study/ethnography/action research Triggers: phenomenology, 현상학, grounded theory, 근거이론, case study, 사례연구, narrative inquiry, ethnography, 민족지, action research, 실행연구, qualitative design
Cross-checks citation keys in index.qmd against references.bib, reporting missing, orphaned, and duplicate entries. Use when verifying citations.
Activate when the user is drafting any academic economics content from scratch (e.g., outlines, abstracts, introductions, data/methods/identification sections, results narratives, conclusions, referee responses, table/figure captions) and needs economics-specific structure, phrasing options, and quality checks to produce publication-ready prose.
Agent A5 - Paradigm & Worldview Advisor - Philosophical foundations for research design. Covers ontology, epistemology, axiology, and methodology alignment. Use when: establishing philosophical foundations, justifying methodological choices, writing positionality statements Triggers: paradigm, 패러다임, ontology, epistemology, worldview, 세계관, philosophical foundations, 철학적 기초
Fills all [FILL:] placeholders across the template to initialize a new research project. Use when setting up a freshly cloned project.
Six-phase protocol for adapting methods across research domains
Generate publication-ready regression tables in LaTeX.
Formats estimation output as a publication-quality regression table with stars, SEs, and fit statistics. Use when creating a results table.
VS-Enhanced Academic Style Humanizer - Transforms writing patterns to achieve authentic scholarly voice Applies transformations from G5 analysis to create natural academic prose Use when: improving AI-assisted writing quality, preparing manuscripts, enhancing scholarly voice Triggers: humanize, transform, make natural, improve writing quality, improve style
Captures tool versions, packages, and kernel info as a reproducibility record in notes/. Use when documenting the environment.
Systematic Review Pipeline Orchestrator - Coordinates systematic literature review automation Manages the complete 7-stage PRISMA 2020 pipeline from research question to RAG system Delegates to specialized agents (I1, I2, I3) while enforcing human checkpoints Use when: conducting systematic reviews, building knowledge repositories, PRISMA automation Triggers: systematic review, PRISMA, literature review automation
Research Guardian - Ethics Advisory & Bias Detection across all research stages Enhanced VS 3-Phase process: Surface-level screening, deep contextual analysis, constructive recommendations Use when: reviewing research ethics, checking for bias, assessing trustworthiness, QRP screening Triggers: ethics review, IRB, bias detection, QRP, trustworthiness, research integrity, p-hacking, HARKing
Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset
Guide for writing the abstract of an academic economics paper. Use this skill whenever the user asks for help writing, drafting, revising, or structuring an abstract for an economics paper - whether empirical micro, development economics, applied economics, or related fields. Also trigger when the user mentions "abstract," "paper summary," or asks how to compress their findings into a short description. This skill synthesizes best practices from David Evans (CGDev), Marc Bellemare, and patterns observed in top economics journals (AER, QJE, AEJ: Applied, etc.).
JASA/Biometrika manuscript structure with VanderWeele notation standards
Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files.
Reads the manuscript and notebooks to generate a structured abstract. Use when writing or updating the abstract.
Drafts academic prose for a manuscript section from bullet points or an outline. Use when writing or expanding a section.
Creates a structured annotation note in references/ with sections for research question, data, findings, and relevance. Use when documenting a paper.
Creates a Quarto revealjs slide deck in slides/ with the project style guide. Use when a presentation is needed.
M-estimation, influence functions, and semiparametric efficiency theory for causal inference
VS-Enhanced Journal Matcher with Journal Intelligence MCP — Real-time journal data pipeline with checkpoint-based human decisions. Uses OpenAlex + Crossref APIs for live metrics. Light VS applied: Avoids IF-centric recommendations + multi-dimensional matching strategy Use when: selecting target journals, planning submissions, comparing publication options Triggers: journal, submission, impact factor, academic journal, publication, submit
VS-Enhanced Academic Style Auditor - Academic Writing Quality Analysis Identifies 24+ writing patterns that reduce scholarly quality, adapted from Wikipedia AI Cleanup guidelines Use when: checking drafts before submission, improving academic writing quality, preparing for style improvement Triggers: writing quality, style audit, pattern check, writing review, academic style check
Publication Specialist - Writing, Review, Pre-registration & Quality Assurance Light VS applied: Avoids template-based writing + audience-specific message design Absorbed G3 (Peer Review Strategist), G4 (Pre-registration Composer), F1-F3 (Quality functions) capabilities Use when: writing abstracts, creating summaries, peer review response, pre-registration, reporting checklists, reproducibility Triggers: abstract, plain language, press release, summary, communication, peer review, revision, pre-registration, OSF, PRISMA, CONSORT, reproducibility
E1-Quantitative Analysis Guide with Code Generation & Sensitivity Analysis VS-Enhanced with Full 5-Phase process: Avoids obvious analyses, explores innovative methodologies Expanded to include qualitative analysis (thematic, grounded theory, content, narrative) Absorbed E4 (Analysis Code Generator) and E5 (Sensitivity Analysis - Primary Study) capabilities Use when: selecting statistical/qualitative methods, interpreting results, checking assumptions, generating code, sensitivity analysis Triggers: statistical analysis, ANOVA, regression, t-test, power analysis, assumption checking, effect size, thematic analysis, grounded theory, content analysis, narrative analysis, NVivo, ATLAS.ti, coding, qualitative data, R code, Python code, SPSS syntax, sensitivity analysis, robustness check
Diverga Dashboard - Live configuration status and feature overview. 24 specialized agents across 9 categories for social science research. VS methodology prevents mode collapse. Human checkpoints enforce human-in-the-loop decisions. Triggers: /diverga, diverga dashboard, diverga status
VS-Enhanced Quantitative Design Consultant with Materials & Sampling Enhanced VS 3-Phase process: Avoids obvious experimental designs, proposes context-optimal quantitative strategies Absorbed C4 (Experimental Materials Developer) and D1 (Sampling Strategy Advisor) capabilities Use when: selecting quantitative research design, planning experimental/survey methodology, power analysis, developing materials, sampling Triggers: RCT, quasi-experimental, experimental design, survey design, power analysis, sample size, factorial design, materials, stimuli, sampling strategy
VS-Enhanced Literature Review Strategist - Comprehensive support for multiple review methodologies Full VS 5-Phase process: Prevents Mode Collapse and presents creative search strategies Supports: Systematic Review (PRISMA 2020), Scoping Review (JBI/PRISMA-ScR), Meta-Synthesis, Realist Synthesis, Narrative Review, Rapid Review Use when: conducting any type of literature review, systematic reviews, meta-analyses, scoping reviews, finding prior research Triggers: literature review, PRISMA, systematic review, scoping review, meta-synthesis, realist synthesis, narrative review, rapid review
Meta-Analysis Master with Data Integrity, Effect Size, Error Prevention & Sensitivity Multi-gate validation and workflow orchestration for meta-analysis. Absorbed C6 (Data Integrity Guard), C7 (Error Prevention Engine), B3 (Effect Size Extractor), E5 (Sensitivity Analysis - Meta) capabilities Triggers: meta-analysis, pooled effect, heterogeneity, forest plot, funnel plot, Hedges g, data integrity, effect size extraction, sensitivity analysis
VS-Enhanced Evidence Quality Appraiser - Prevents Mode Collapse with context-adaptive quality assessment Enhanced VS 3-Phase process: Avoids automatic tool application, delivers research-specific evaluation strategies Use when: appraising study quality, assessing risk of bias, grading evidence Triggers: quality appraisal, RoB, GRADE, Newcastle-Ottawa, risk of bias, methodological quality
VS-Enhanced Research Question Refiner - Prevents Mode Collapse and derives differentiated research questions Enhanced VS 3-Phase process: Modal question avoidance, alternatives presentation, differentiated RQ recommendation Use when: refining research ideas, formulating research questions, clarifying scope Triggers: research question, 연구 질문, PICO, SPIDER, research idea
Fetch economic data from FRED, World Bank, and other APIs
Generates robustness check code and formats results as a combined table. Use for sensitivity analysis.
Design and document statistical algorithms with pseudocode and complexity analysis
Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말
Agent C3 - Mixed Methods Design Consultant Comprehensive mixed methods research design specialist covering sequential, concurrent, embedded, and multiphase designs with Morse notation. Core Capabilities: - Sequential Explanatory (QUAN → qual): Explain quantitative results - Sequential Exploratory (QUAL → quan): Develop instruments - Convergent Parallel (QUAN + QUAL): Comprehensive understanding - Embedded (QUAN(qual)): Secondary strand addresses different question - Multiphase: Long-term projects with iterative phases - Morse notation interpretation and recommendation
Agent E3 - Mixed Methods Integration Specialist - Qual-Quant data integration and meta-inference. Covers joint display creation, integration strategies, and legitimation techniques.
Converts LaTeX article-class .tex documents to Quarto .qmd format for multi-format publishing (HTML, PDF, Word). Use when asked to convert, port, migrate, or translate a .tex LaTeX file to Quarto; when porting an academic paper or manuscript from LaTeX to Quarto; when a .tex document needs to render to HTML, Word, or Typst PDF. Covers preamble → YAML front matter, section headings, text formatting, math, citations (natbib/biblatex), cross-references, figures, tables, lists, footnotes, hyperlinks, and special characters.
Assesses a research paper outline (.qmd file) against structured criteria from Kosuke Imai's empirical research guide. Evaluates the abstract and section outline for: research question clarity, stated contributions, hypotheses and testable implications, data description, planned results and inferential approach, and robustness checks. Detects causal papers from the abstract and conditionally assesses identification strategy only when causal framing is present. Produces a structured markdown report with PASS/PARTIAL/FAIL assessments and actionable suggestions. Use when asked to assess, evaluate, review, or check a paper outline, abstract-and-outline, or research plan in a .qmd file.
Takes a proofread or apsa-style report file (or any markdown file using **Original:** / **Recommended:** syntax) and rewrites the original source file with git merge conflict markers so the user can accept or reject each suggested edit using VS Code or Positron's built-in merge conflict UI. Branch names are "original" and "claude-edits". Use when asked to apply edits, insert conflict markers, or set up merge resolution for a copy-edit report. Supports an optional @sec-label argument to restrict markers to one section.
Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name.
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, and Socratic guided modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review.
STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.
Translates LaTeX documents (.tex) to Typst (.typ), focusing on article-class documents. Use when asked to convert, port, migrate, or translate LaTeX to Typst. Covers document structure, text formatting, page layout, math equations and symbols, figures, tables, TikZ-to-CeTZ diagrams, bibliography, cross-references, footnotes, and code blocks. Includes comprehensive symbol mapping tables.
APSA style checker for Quarto (.qmd) files. Checks numbers, capitalization, abbreviations, italics, in-text citations, titles of works, neutral and unbiased language, and APSA-specific terminology against the APSA Style Manual for Political Science (2018, updated 2023). Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to check APSA style, fix citations, review capitalization, check number formatting, or flag biased language in a .qmd document. For grammar, spelling, and punctuation, use the proofread skill instead. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.
Unwraps hard-wrapped markdown files so that each sentence ends with a newline instead of mid-sentence line breaks. Joins continuation lines within a paragraph into single lines, then re-breaks at sentence boundaries (period, question mark, exclamation point). Preserves blank lines, headings, fenced code blocks, block quotes, and list items. Use when asked to unwrap text, fix line breaks, reflow sentences, or clean up hard-wrapped markdown or .qmd files.
Academic paper writing skill with 12-agent pipeline. v2.5: Style Calibration (learn author's writing voice from past papers) + Writing Quality Check (writing quality checklist for natural prose). Supports IMRaD, literature review, theoretical, case study, policy brief, and conference paper structures. APA 7.0 (default), Chicago, MLA, IEEE, Vancouver citation formats. Bilingual abstracts (zh-TW + EN). Multi-format output (LaTeX, DOCX, PDF, Markdown). Triggers on: write paper, academic paper, paper outline, write abstract, revise paper, check citations, convert to LaTeX, guide my paper, parse reviews, revision roadmap, 寫論文, 學術論文, 論文大綱, 寫摘要, 修改論文, 檢查引用, 引導我寫論文, 帶我規劃論文, 逐章規劃, 論文架構, 審查意見, 修訂路線圖.
Prose quality checker for Quarto (.qmd) files, grounded in William Zinsser's *On Writing Well* (30th Anniversary Edition). Checks for clutter, weak verbs, hollow qualifiers, clichés, inflated academic voice, poor leads and endings, pronoun and tense inconsistency, and unclear explanation. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to improve prose quality, tighten writing, reduce clutter, or apply Zinsser's writing principles to a draft. For grammar and punctuation, use the proofread skill. For APSA style rules, use the apsa-style skill. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 9-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Expert copy editor for Quarto (.qmd) files. Checks grammar, spelling, punctuation, and academic writing quality. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to proofread, check grammar, fix typos, or review prose in a .qmd document. For APSA style rules (numbers, citations, capitalization, abbreviations, neutral language), use the apsa-style skill instead. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.
Use when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative economic data analysis
Production-grade Bayesian causal inference with PyMC, CausalPy, and DoWhy. Enforces DAG-first thinking, mandatory user checkpoints for assumptions, design-specific refutation, and defensible reporting with causal language guardrails. Trigger on: causal inference, causal effect estimation, treatment effects, counterfactuals, difference-in-differences (DiD), synthetic control, regression discontinuity (RDD), interrupted time series (ITS), instrumental variables (IV), propensity scores, DAGs, causal graphs, confounders, backdoor criterion, do-calculus, interventional distributions, pm.do(), pm.observe(), CausalPy, DoWhy, mediation analysis, refutation, sensitivity analysis, parallel trends, placebo tests, or any question of the form "does X cause Y" or "what is the effect of X on Y."
Cleans a Quarto (.qmd) file by replacing LaTeX holdovers with proper Quarto/Pandoc syntax so the document renders correctly to HTML, PDF (Typst/LaTeX), and Word. Fixes citations (\citep → [@key]), cross-references (\ref → @label), figures (\includegraphics → markdown), tables, text formatting (\textbf → **bold**), inline math (\( \) → $ $), hyperlinks (\href → [text](url)), footnotes (\footnote → ^[]), list environments, section headings, and R Markdown chunk options (dot-style → #| YAML). Use when asked to clean, fix, modernize, or port a Quarto or R Markdown document; when LaTeX commands appear in a .qmd file; when a document fails to render to Word or Typst; or when citations/cross-references do not appear in non-LaTeX output.
Writes expert academic paper summaries for social science research, particularly political science and applied statistics. Use when asked to summarize, review, or create a reading summary of an academic paper, PDF, or research article. Accepts a file (PDF or text format) or a directory of papers. Produces a structured markdown summary — approximately 400–600 words — covering primary contributions, major questions and answers with point estimates, methods and data, and limitations and robustness. Includes BibTeX citation retrieved from Google Scholar and keyword metadata.
Complex survey analysis: strata/PSU/weights, variance estimation (Taylor, BRR, jackknife, bootstrap), survey GLM, domain analysis, calibration. Polars-native. Use for NHANES, CPS, ACS PUMS, BRFSS, DHS. Non-survey regression: statsmodels/pyfixest.
Fast high-dimensional fixed effects: OLS, Poisson, IV with multi-way FE; DiD (TWFE, did2s, Sun-Abraham); clustered SEs; etable/coefplot/iplot. Use for FE regressions or DiD. For panel RE/between use linearmodels; for GLM without FE use statsmodels.
Stata-to-Python translation for data analysis. Maps Stata commands (reghdfe, xtreg, ivregress, margins, esttab, svy:) to Python (polars, pyfixest, statsmodels, svy). Use when user has Stata background or requests Stata-equivalent code comments.
Guide for creating and auditing DAAF skills (SKILL.md). Covers frontmatter, metadata vocabulary, progressive disclosure, decision trees, reference files. Use when creating, reviewing, or debugging skill loading. For agent files, use agent-authoring.
R-to-Python translation for data analysis. Maps R packages (tidyverse, ggplot2, fixest, survey, sf, plm) to Python equivalents (polars, plotnine, pyfixest, svy, geopandas). Use when user has R background or requests R-equivalent code comments.
Statistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics. Formula API. Use for regressions without fixed effects, GLMs, or time series. For FE/DiD use pyfixest; panel/IV use linearmodels.
Translating technical findings for non-technical audiences. Narrative frameworks (Pyramid Principle, SCQA), plain-language translation, executive summaries, policy briefs, causal language. Use when presenting to stakeholders or reviewing deliverables
Machine learning: clustering, PCA/t-SNE/UMAP, classification, prediction regression (Ridge/Lasso/ensemble), cross-validation, Pipelines. For unsupervised analysis, classification, or prediction. For econometric regression use pyfixest/statsmodels.
FSA — Title IV aid at institution level (~5,500 institutions, 1999-2021). Pell Grants, Direct/PLUS loans, campus-based aid, financial responsibility scores, 90/10 metrics. Use for aid distribution, loan volume, or for-profit analysis. By unitid.
SAIPE — annual Census poverty estimates for school districts (Portal; county/state not in Portal). Use for district poverty, Title I context, or trends. ~18-month lag. No race/ethnicity disaggregation at district level — use ACS 5-year for that.
Polars DataFrame library for high-performance data manipulation. Lazy/eager execution, expressions, I/O (CSV, Parquet, JSON), aggregations, joins, string/datetime ops, pandas interop. Use for Polars DataFrames or reading/writing Parquet files.
Downloads education datasets from configured mirror sources (parquet/CSV) with local Polars filtering. Use when writing fetch scripts or retrieving CCD, IPEDS, CRDC, SAIPE data. Load after education-data-explorer — retrieval here, not discovery.
MEPS — Urban Institute modeled school-level poverty (% at 100% FPL), from CCD + SAIPE (public schools, 2009-2022, 2-3yr lag). Use when FRPL is unreliable due to CEP. Consistent cross-state measurement. Public schools only.
NACUBO endowment data (~650 institutions, 2012-2022). Portal: 7 columns only (total endowment, per-FTE, YoY change). Use for endowment size/trends. Full investment/spending needs direct NACUBO access. For all-institution coverage use IPEDS finance.
Panel data, IV/GMM, system regression. PanelOLS (FE/RE), BetweenOLS, Fama-MacBeth, IV2SLS/LIML/GMM, SUR, 3SLS, Driscoll-Kraay SEs. Use for RE/between, system estimation, or GMM. Complements pyfixest (FE + DiD) and statsmodels (GLM + time series).
CCD — federal universe of all U.S. public K-12 schools (~100K) and districts (~18K). Enrollment, staffing, finance, directory data (1986-present). Use for public school analysis by grade/race/sex. Public only; excludes private and postsecondary.
Plotly interactive visualization. Express and Graph Objects: scatter, line, bar, heatmap, 3D, geographic charts; subplots; styling; export. Use when interactivity (hover/zoom) is needed. For static figures use plotnine; for GIS use geopandas.
plotnine static visualization (ggplot2 syntax for Python). Geoms, aesthetics, scales, coordinates, facets, themes. Use for static publication-quality figures with grammar-of-graphics syntax. For interactive charts use plotly; for maps use geopandas.
EDFacts — K-12 outcomes: assessment proficiency, ACGR graduation rates, ESSA accountability at school/district level (2009-2020). Within-state trends and subgroup gaps. Complements CCD with outcome data. Cannot compare across states — use NAEP.
PSEO — Census data linking graduates to employment via LEHD wage records. Earnings percentiles at 1/5/10 years post-graduation by institution, degree, CIP. Use for graduate earnings analysis. Coverage: ~29% of graduates from ~31 states.
Spatial data: GeoDataFrames, spatial joins, CRS/projections, choropleth/interactive maps, spatial autocorrelation, PySAL. Use for geographic data, spatial files (Shapefile, GeoPackage, GeoParquet), or spatial stats. For charts without GIS use plotly.
EADA — college athletics gender equity (~2,000+ institutions, 2002-2021). Participation, coaching, salaries, expenses, revenues, athletic aid by gender. Not Title IX compliance data. No sector column; join IPEDS on unitid for institution type.
Reactive Python notebook system. Cell reactivity, UI elements (sliders, dropdowns, tables), SQL cells, plotting, app deployment. Use when assembling Stage 9 notebooks, building data apps, or converting Jupyter to marimo .py format.
County Presidential Returns 2000-2024 (MIT MEDSL). Vote shares, party trends, turnout by county_fips (joins census/education data). Requires HARVARD_DATAVERSE_API_KEY. Critical: mode='TOTAL' drops ~1K counties post-2020 — use 3-pattern reconstruction
NHGIS — census geography crosswalks via Portal: links schools (ncessch) and colleges (unitid) to tracts, block groups, CBSAs (1990-2020). Census demographics NOT in Portal — access NHGIS directly. Use for linking education data to census geography.
College Scorecard — post-enrollment outcomes linking aid records to IRS/Treasury earnings. Earnings, loan repayment, debt via six Portal sub-datasets. Use when tax-record-based earnings needed. Tracks only Title IV aid recipients, not all students.
IPEDS — primary federal postsecondary data (~6,500 institutions, 1980-present): enrollment, completions, graduation rates, finance, aid, admissions, HR. For college/university analysis. Grad rates = first-time full-time; finance needs GASB/FASB care.
CRDC — biennial OCR survey of all U.S. public schools (2011-2021). Discipline, course access, harassment, restraint/seclusion by race/sex/disability/EL. Use for civil rights and equity analysis. 2020-21 COVID-impacted; 2011-14 sampled, not universe.
NCCS — Form 990 data for private nonprofit colleges (Portal: IPEDS-matched, 1993-2016). Revenue, expenses, assets, endowment, governance beyond IPEDS. Use when IRS financial depth needed. Portal ends 2016; public institutions excluded (no Form 990).
CSS — annual Clery Act crime/fire safety for Title IV institutions. Portal: hate crimes only (2005-2021); primary offenses, VAWA, arrests, fire safety need ope.ed.gov directly. Use for campus crime analysis. Identified by IPEDS unitid.
Discovers education data from Urban Institute Portal: endpoints, variables, year coverage, join keys (CCD, IPEDS, CRDC, Scorecard, SAIPE). Use to map questions to data. Load before education-data-query — discovery here, download there.
Multi-agent slide review (visual, pedagogy, proofreading). Use for comprehensive quality check before milestones.
Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files.
Validate bibliography entries against citations in all manuscript files. Find missing entries and unused references.
Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files.
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
Run the Julia code review protocol on Julia scripts. Checks code quality, type stability, parallel computing patterns, and scientific computing standards. Produces a report without editing files.
This skill should be used when the user asks to "implement a DiD regression", "write a causal inference pipeline", "set up an event study", "implement instrumental variables", "run a regression discontinuity design", "build a synthetic control model", "implement propensity score matching", "write parallel trends test", "implement Bacon decomposition", or needs code templates for causal inference methods in Python, R, or Stata. Based on Scott Cunningham's Causal Inference: The Mixtape.
Compile a Beamer LaTeX slide deck with XeLaTeX (3 passes + bibtex). Use when compiling lecture slides.
Julia-based econometric and structural estimation for computationally intensive tasks. Use for structural models, maximum likelihood, GMM, numerical optimization, simulations, and high-performance computing. Covers DataFrames.jl, FixedEffectModels.jl, Optim.jl, and performance optimization.
Comprehensive manuscript review covering argument structure, identification strategy, econometric specification, citation completeness, and potential referee objections.
Data science methodology for Python research: EDA, validation, causal inference (IV, DiD, RD, synthetic control), clustering/PCA/UMAP, supervised ML, geospatial, visualization. Method selection guidance. For syntax, load tool-specific skills.
Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset.
Operational framework for the DAAF orchestrator. Defines engagement modes, confirmation protocol, subagent dispatch, context budget, and reference-loading. Loaded exclusively by the orchestrator — not for subagents or user questions.
Adversarial Quarto vs Beamer QA. Critic finds issues, fixer applies fixes, loops until APPROVED (max 5 rounds).
End-to-end R data analysis workflow from exploration through regression to publication-ready tables and figures
End-to-end R data analysis workflow from exploration through regression to publication-ready tables and figures.
Draft academic paper sections with notation protocol, anti-hedging, and humanizer pass. Replaces /draft-paper and /humanizer.
Agent-native one-stop toolkit for the full empirical data-analysis pipeline in Python (v1.6+). 900+ functions, one import (`import statspai as sp`), unified API. Covers the complete loop after data cleaning — descriptive stats & EDA (sp.sumstats, sp.balance_table, sp.balance_panel), estimand-first research-question DSL (sp.causal_question), LLM-assisted DAG discovery (sp.llm_dag_propose/validate/constrained), one-call orchestration (sp.causal), classical estimators (OLS, IV, DID, staggered DID, RDD, PSM, SCM), ML causal (DML, Causal Forest, Meta-Learners, TMLE), neural causal, text causal (sp.causal_text), and diagnostics + robustness (sp.diagnose, sp.spec_curve, sp.honest_did). Use when the user asks to run a full empirical analysis, decide which estimator to use ("DID vs RD vs IV?"), explore models via DAG, estimate treatment effects, evaluate policy, run observational studies, or apply any of the listed econometric methods in Python. Every function returns structured result objects with self-describing schemas for LLM-driven workflows. Data cleaning (missing values, type coercion, merges) is *not* covered — handle that with pandas first, then enter StatsPAI.
Execute research implementation plans efficiently while maintaining estimation quality and finishing features
Run multi-agent econometric review on estimation code, identification arguments, and research artifacts
Divergent research ideation — generate many candidate directions, then adversarially filter to the strongest
Document a recently solved research problem to compound methodological knowledge
Submission pipeline — journal targeting, replication package, audit, and final gate. Replaces /submit, /target-journal, /audit-replication, /data-deposit.
End-to-end data analysis dispatching Coder and Data-engineer for implementation, coder-critic for review. Supports R, Stata, Python, Julia. Replaces /data-analysis.
Run the proofreading protocol on manuscript files. Checks grammar, typos, overflow, consistency, and academic writing quality. Produces a report without editing files.
Run IV, DiD, and RDD analyses in R with proper diagnostics. Use when implementing causal inference methods, event studies, or treatment effect estimation.
Stage, commit, create PR, and merge to main. Use for the standard commit-PR-merge cycle.
Compile a LaTeX manuscript with pdflatex (3 passes + bibtex). Use when compiling the research paper.
Extract TikZ diagrams from Beamer source, compile to PDF, convert to SVG with 0-based indexing. Use when updating TikZ diagrams for Quarto slides.
Explore methodological approaches through structured analysis before planning implementation
Extract reusable knowledge from the current session into a persistent skill. Use when you discover something non-obvious, create a workaround, or develop a multi-step workflow that future sessions would benefit from.
Structured literature search and synthesis with citation extraction and gap identification
Run the proofreading protocol on lecture files. Checks grammar, typos, overflow, consistency, and academic writing quality. Produces a report without editing files.
Show current context status and session health. Use to check how much context has been used, whether auto-compact is approaching, and what state will be preserved.
Guide for creating DAAF agent definition files. Covers 12-section template, hook registration, skills-in-frontmatter, integration checklist. Use when adding or revising agents. For SKILL.md files, use skill-authoring instead.
Challenge slide design with 5-7 pedagogical questions. Checks ordering, prerequisites, and cognitive load.
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).
Perform adversarial visual audit of Quarto or Beamer slides checking for overflow, font consistency, box fatigue, and layout issues.
Translate Beamer LaTeX to Quarto RevealJS. Multi-phase workflow with TikZ extraction and QA.
Comprehensive manuscript review covering argument structure, econometric specification, citation completeness, and potential referee objections
Transform research descriptions into well-structured implementation plans following project conventions
Stage, commit, create PR, and merge to main. Use for the standard commit-PR-merge cycle.
Create new Beamer lecture from papers and materials. Guided workflow with notation consistency.
R&R cycle — classify referee comments and route to appropriate agents. Replaces /respond-to-referee.
Challenge research design decisions, assumptions, and methodology choices with specific critical questions. Helps strengthen the paper before submission.
All quality reviews — routes to appropriate critics based on target file type and flags. Replaces /paper-excellence, /proofread, /econometrics-check, /review-r, /review-paper.
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
R-based econometric analysis for academic research. Use when writing R code for panel data, difference-in-differences, instrumental variables, spatial econometrics, or regression analysis. Covers data.table, fixest, sf, modelsummary, and publication-ready outputs.
Discovery phase combining research interviews, literature search, data discovery, and ideation. Routes to appropriate agents based on arguments. Replaces /interview-me, /lit-review, /find-data, /research-ideation.
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy.
Structured literature search and synthesis with citation extraction and gap identification.
Full research pipeline from idea to paper. Orchestrates all phases — discovery, strategy, analysis, writing, peer review, and submission. Use when starting a new research project from scratch.
Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset
Validate bibliography entries against citations in all lecture files. Find missing entries and unused references.
Utility commands — commit, compile, validate-bib, journal, context-status, deploy, learn. Replaces individual utility skills.
Deep consistency audit of the entire repository infrastructure. Launches 4 parallel specialist agents to find factual errors, code bugs, count mismatches, and cross-document inconsistencies. Then fixes all issues and loops until clean. Use when: after making broad changes, before releases, or when user says "audit", "find inconsistencies", "check everything".
Interpretation guidance for Urban Institute Portal datasets. Coded values (-1/-2/-3), year definitions, grade encoding, suppression, licensing, cross-source joins. Use when interpreting Portal data before analysis. Routes to source-specific skills.
Run holistic pedagogical review on lecture slides. Checks narrative arc, student prerequisites, worked examples, notation clarity, and deck pacing.
Design identification strategy or pre-analysis plan. Dispatches Strategist (proposer) and strategist-critic (validator). Replaces /identify and /pre-analysis-plan.
Render Quarto slides and sync to docs/ for GitHub Pages deployment. Use when deploying lecture slides after making changes.
Create and audit presentations (Beamer or Quarto RevealJS). Combines talk creation, visual audit, and compilation. Replaces /create-talk, /visual-audit, /compile-latex (for talks).
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 17+ community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code.
Find and fix technical debt including duplicated code, dead code, outdated patterns, and code smells. Run at the end of sessions to clean up.
Clean and transform messy data in Stata with reproducible workflows
This skill covers applied microeconomic empirical methods and research design. Use when the user is selecting an identification strategy, comparing estimators, running diagnostics, designing a research study, or evaluating an empirical strategy. Triggers on "which method", "what estimator", "how to choose", "method comparison", "empirical strategy", "research design", "applied micro", "identification strategy", "power analysis", "design-based", "model-based", "minimum detectable effect", "specification".
Draft economics papers with proper structure and academic style
Agent-native causal inference & econometrics toolkit for Python. 390+ functions, one import, unified API. Covers OLS, IV, DID, staggered DID, RDD, PSM, SCM, DML, Causal Forest, Meta-Learners, TMLE, neural causal models, and more. Every function returns structured result objects with self-describing schemas for LLM-driven workflows.
Panel data analysis with Python using linearmodels and pandas.
Run a structural estimation pipeline — routes to /workflows:work with estimation context from empirical-playbook
Run IV, DiD, and RDD analyses in R with proper diagnostics
Create academic presentations in Beamer with professional themes
Full autonomous research workflow using swarm mode for parallel execution
This skill covers publication-quality tables and figures for academic research papers. Use when formatting regression results, summary statistics, Monte Carlo output, or research visualizations for LaTeX inclusion. Triggers on "table", "figure", "tabulate", "stargazer", "publication-ready", "LaTeX table", "event study plot", "coefficient plot", "RD plot", "power curve", "specification curve", "binscatter", "format results", "booktabs".
Build and verify replication packages — routes to reproducibility-auditor agent
Commit changes, push to remote, and create a pull request. Use for completing features or fixes ready for review.
Generate research questions from economic phenomena
Generate publication-ready regression tables in LaTeX.
This skill covers academic journal submission, referee responses, and revision management. Use when the user is preparing a manuscript for submission, formatting for a specific journal, responding to referees, or managing revisions. Triggers on "submit", "referee", "revision", "R&R", "response letter", "journal", "formatting", "submission", "resubmit", "cover letter", "referee report", "revise and resubmit".
Build and solve Walrasian general equilibrium models with theory derivations and Julia computation
Implements the Spec-Driven Development lifecycle (Intent, Requirements, Design, Tasks, Build) for structured feature development. Use when the user wants to scaffold a new feature spec, generate EARS requirements, create a technical design, break work into tasks, or check spec status. Trigger on keywords: sdd, spec-driven, ears requirements, feature spec.
Run regression analyses in Stata with publication-ready output tables.
This skill covers structural econometric models. Use when the user is building, estimating, or debugging structural models — including BLP demand estimation, dynamic discrete choice, auction models, or any workflow involving moment conditions, nested fixed-point algorithms, or MPEC formulations. Triggers on "structural model", "moment conditions", "NFXP", "MPEC", "BLP", "random coefficients", "dynamic discrete choice", "CCP", "Rust model", "auction estimation", "GMM objective", "inner loop", "contraction mapping", or convergence/starting value problems in optimization-based estimation.
Create publication-quality charts and graphs for economics papers.
Simplify and clean up code after changes are complete. Reduces complexity, improves readability, and ensures consistency.
Full autonomous research workflow — brainstorm, plan, implement, review, and document
This skill covers causal inference methods in observational and quasi-experimental settings. Use when the user is implementing, choosing between, or debugging causal identification strategies — including instrumental variables, difference-in-differences, regression discontinuity, synthetic control, or matching estimators. Triggers on "causal effect", "identification strategy", "instrumental variable", "2SLS", "GMM", "difference-in-differences", "DiD", "staggered treatment", "regression discontinuity", "RDD", "synthetic control", "matching", "propensity score", "IPW", "AIPW", "doubly robust", "LATE", "ATT", "ATE", "parallel trends", "exclusion restriction", "first stage", "weak instruments", or "endogeneity".
Search, summarize, and synthesize economics literature
This skill covers reproducible research pipelines and replication packages. Use when the user is setting up a research project directory structure, configuring workflow managers (Make, Snakemake, DVC), managing computational environments, preparing replication packages for journal submission, or debugging reproducibility failures. Triggers on "reproducible", "replication package", "Makefile", "Snakemake", "DVC", "pipeline", "workflow manager", "data versioning", "conda environment", "Docker", "seed management", "AEA data editor", "replication", "project structure", or "submission checklist".
Write and typeset economic models in LaTeX with proper notation
This skill covers game-theoretic methods in structural econometrics and industrial organization. Use when the user is working with strategic interactions, equilibrium analysis, or game-theoretic structural models — including entry games, conduct testing, auction models with strategic bidding, bargaining, or matching markets. Triggers on "Nash equilibrium", "subgame perfect", "best response", "strategic interaction", "entry game", "conduct testing", "auction", "mechanism design", "matching market", "bargaining", "BNE", "Bayesian Nash", "static game", "dynamic game", "repeated game", "multiple equilibria", "equilibrium selection", "discrete game", "oligopoly", "game-theoretic", "player", "payoff", "strategy", "dominant strategy", "Bresnahan-Reiss", "Ciliberto-Tamer", "partial identification", "set identification", or markup test.
This skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive regression models, cross-fitting, Neyman orthogonality, debiased ML, causal forests, generalized random forest, GRF, honest causal trees, AIPW with machine learning, doubly robust with machine learning, DR-Learner, T-Learner, S-Learner, X-Learner, meta-learners, heterogeneous treatment effects, conditional average treatment effect, CATE, HTE, high-dimensional controls, LASSO controls, post-LASSO, post-double selection, Belloni-Chernozhukov-Hansen, Riesz representer, Chernozhukov, sample splitting, econml, DoubleML package, or any combination of machine learning and causal inference.
This skill covers Bayesian estimation and inference in quantitative social science. Use when the user is specifying priors, running MCMC, diagnosing chain convergence, or reporting posterior summaries — including hierarchical models, Bayesian structural models, and small-sample settings where priors regularize. Triggers on "Bayesian estimation", "Bayesian inference", "MCMC", "Markov chain Monte Carlo", "Stan", "PyMC", "NumPyro", "prior", "posterior", "credible interval", "Bayesian structural", "Bayesian BLP", "Bayesian DSGE", "hierarchical model", "random effects Bayesian", "posterior predictive check", "Bayes factor", "prior predictive check", "NUTS", "HMC", "Hamiltonian Monte Carlo", "R-hat", "rhat", "effective sample size", "ESS", "Bayesian calibration", "posterior distribution", "prior elicitation", "weakly informative prior", "brms", "rstanarm", "cmdstanpy", "pymc", "arviz".
Fetch economic data from FRED, World Bank, and other APIs
This skill covers formal identification arguments and proofs in structural and reduced-form econometrics. Use when the user needs to prove or formalize that a parameter is identified — including writing identification propositions, stating regularity conditions, deriving rank conditions, or showing observational equivalence fails. Triggers on "identification proof", "identification argument", "identify the parameter", "show identification", "identification condition", "exclusion restriction proof", "rank condition", "order condition", "identification strategy formal", "nonparametric identification", "parametric identification", "local identification", "global identification", "observational equivalence", "identification at infinity", "completeness condition", "regularity conditions", "Rothenberg", "proof of identification", "identification result", "identified parameter", "point identified", "set identified", "partial identification".