skills/29-quarcs-lab-project20XXy/dot-claude/skills/literature-note/SKILL.md
Creates a structured annotation note in references/ with sections for research question, data, findings, and relevance. Use when documenting a paper.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research literature-noteInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Create a structured annotation note for a paper in references/.
$ARGUMENTS — a citation key from references.bib, a DOI, or a paper description (e.g., "acemoglu2001colonial" or "Acemoglu 2001 colonial origins")Parse the argument:
references.bib, use that entry's metadatareferences.bib first (offer to run the /project:cite workflow)If a URL or DOI is provided, attempt to fetch and read the paper to extract key information.
Create a Markdown file in references/ named <citation-key>.md with this structure:
# <Author (Year)> — <Short Title>
**Citation key:** `<key>`
**Full reference:** <formatted reference>
## Research Question
[What question does this paper address?]
## Identification Strategy
[How do the authors establish causality? What is the main source of variation?]
## Data and Sample
[What data do they use? What is the sample period, unit of observation, and sample size?]
## Key Findings
- [Finding 1]
- [Finding 2]
- [Finding 3]
## Methodology Notes
[Econometric methods, estimators, robustness checks worth noting]
## Relevance to This Project
[How does this paper relate to the current research? What can we build on or contrast with?]
If information about the paper was retrieved (from the web or a PDF), pre-fill the sections with extracted content. Otherwise, leave the bracket placeholders for the user to fill in.
Report the file path and remind the user to fill in any remaining placeholder sections.
references.bib and cannot be resolved, ask the user for more details.references/<key>.md already exists, show the existing note and ask if the user wants to update it.tools
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.