skills/67-econfin-workflow-toolkit/significance-search/SKILL.md
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".
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research Significance-SearchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
This skill generates a parallelised Stata .do file that:
tuplesreghdfe (or user-specified command) for each combination across N parallel Stata instancesImportant: This skill only generates the .do file. It does NOT execute it. Tell the user the output path and let them run it in Stata themselves.
Ask the user for the following. Items marked (required) must be provided; others have defaults.
| Parameter | Description | Default |
|---|---|---|
| data file (required) | Full path to the .dta file | -- |
| dependent variable (Y) (required) | Y variable name | -- |
| independent variable (X) (required) | X variable of interest | -- |
| cluster variable (required) | Variable for clustering SE and fixed effects | -- |
| mandatory controls (required) | Controls always included | -- |
| optional controls (required) | Controls to search over (all subsets) | -- |
| N_WORKERS | Number of parallel Stata instances | 8 |
| significance level | Two-tailed alpha | 0.01 |
| model command | Estimation command | reghdfe |
| absorb | Fixed effects specification | absorb(<<CLUSTER>> year) |
| vce | Variance-covariance specification | vce(cluster <<CLUSTER>>) |
| STATA_EXE | Path to Stata executable | E:\Stata\StataMP-64.exe |
tuples generates 32,768+ combinations
and will freeze Stata. If the user provides more than 14, warn them and ask them to reduce or move
some into mandatory controls.<data_dir>\控制变量搜索_并行.do by default, placed next to the data file.After collecting parameters:
C:\Users\Verasuna\.claude\skills\ControlVariable\template.do<<PLACEHOLDERS>> with user-provided values (see table below)<data_dir>\控制变量搜索_并行.doDo not modify any code logic in the template. Only replace placeholders.
<<N_WORKERS>> e.g. 8
<<STATA_EXE>> e.g. E:\Stata\StataMP-64.exe
<<PROJ_DIR>> directory containing the .dta file
<<DATA_FILE>> filename of .dta (just the name, not full path)
<<SIGNIFICANCE>> e.g. 0.01
<<DEP_VAR>> dependent variable (Y)
<<INDEP_VAR>> independent variable (X)
<<MANDATORY_CONTROLS>> space-separated mandatory controls
<<OPTIONAL_CONTROLS>> space-separated optional controls
<<MODEL_CMD>> e.g. reghdfe
<<MODEL_ABSORB>> e.g. absorb(stkcd year)
<<MODEL_VCE>> e.g. vce(cluster stkcd)
<<HEARTBEAT_STALL>> 300
User says: "Y是GTFPEFF8,X是Size,聚类到stkcd,必选控制变量Lev,可选控制变量ROA ROE ATO Cashflow,数据文件是 C:\data\mydata.dta"
Then fill:
<<DEP_VAR>> = GTFPEFF8<<INDEP_VAR>> = Size<<MODEL_ABSORB>> = absorb(stkcd year)<<MODEL_VCE>> = vce(cluster stkcd)<<MANDATORY_CONTROLS>> = Lev<<OPTIONAL_CONTROLS>> = ROA ROE ATO Cashflow<<PROJ_DIR>> = C:\data<<DATA_FILE>> = mydata.dtatools
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」)。
development
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.
documentation
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.
tools
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.