Agent skill · Code Review & Quality

review-paper-code

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.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codecan modify filesNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill review-paper-code --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 11 KB
Bundled scripts: none
Allowed tools: ReadWriteEditGlobGrepBashAgent
Path: skills/21-claesbackman-AI-research-feedback/Skills/review-paper-code/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Review Paper Code Review a research project's paper and code for reproducibility, code quality, and paper-code alignment. Be constructive, concrete, and calibrated. Treat gaps as items to verify, not accusations. ## Scope This skill supports: - LaTeX papers - Stata (`.do`), R (`.R`, `.r`), and Python (`.py`) code Default review depth: - `main`: prioritize the main paper, main scripts, and core o

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About this skill
What does the review-paper-code skill do?

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.

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill review-paper-code --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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