skills/29-quarcs-lab-project20XXy/dot-claude/skills/data-audit/SKILL.md
Scans notebooks for data file references and verifies each file exists on disk. Use when checking for broken data paths.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research data-auditInstall 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.
Scan all notebooks for data file references and verify they exist on disk.
Scan all .ipynb files in notebooks/ for data loading patterns:
pd.read_csv(...), pd.read_stata(...), pd.read_excel(...), pd.read_parquet(...), open(...), np.loadtxt(...)read.csv(...), read_csv(...), read.dta(...), haven::read_dta(...), readxl::read_excel(...), load(...)use "...", import delimited "...", import excel "...", insheet using "...".md Jupytext pairs for the same patternsExtract every referenced file path and normalize it:
notebooks/)DATA_DIR, RAW_DATA_DIR from config.py / config.RCheck that each referenced file exists in data/rawData/ or data/
Scan data/rawData/ and data/ for all data files present on disk
Report three categories:
Resolved — referenced and found:
Broken — referenced but not found:
Undocumented — on disk but never referenced by any notebook:
data/rawData/ or data/ that no notebook loadsPrint a summary: total references, resolved, broken, undocumented files
data/rawData/ does not exist, warn but continue checking data/.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.