Agent skill · Code Review & Quality

stata-modernize

Improve, modernize, and optimize existing Stata code for performance, portability, and maintainability. Use when legacy patterns such as preserve/restore, cd, #delimit, slow aggregation, or weak fixed-effects workflows appear in code under review.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill stata-modernize --agent claude-code

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

Facts
Files in the skill folder: 4
SKILL.md size: 1 KB
Bundled scripts: none
Path: skills/64-tmonk-mcp-stata/skills/stata-modernize/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

# Modernize Stata Use this skill when a user wants stronger Stata code, not just working Stata code. 1. Identify the current anti-patterns. 2. Recommend or implement modern replacements with clear rationale. 3. Favor frames, `reghdfe`, `gtools`, portable paths, and explicit state handling. Read `references/patterns.md` for common replacements and examples.

More from Auto-Empirical-Research-Skills
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About this skill
What does the stata-modernize skill do?

Improve, modernize, and optimize existing Stata code for performance, portability, and maintainability. Use when legacy patterns such as preserve/restore, cd, #delimit, slow aggregation, or weak fixed-effects workflows appear in code under review.

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill stata-modernize --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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