Agent skill · AI & Agents

stata-environment-diagnose

Diagnose local Stata, MCP, package, startup, graph-export, and permissions issues. Use when setup is failing, Stata is not discovered, packages are missing, logs are truncated, or a managed machine behaves differently from a normal workstation.

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

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

Facts
Files in the skill folder: 5
SKILL.md size: 1 KB
Bundled scripts: yes
Path: skills/64-tmonk-mcp-stata/skills/stata-environment-diagnose/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

# Environment Diagnose Use this skill for setup and platform troubleshooting. 1. Verify detection with `stata_manage_session(action="detect")`. 2. Reproduce the smallest failing command. 3. Use logs, package checks, and environment reporting before suggesting a fix. 4. Separate root cause, evidence, remediation, and verification. Read `references/troubleshooting.md` for the diagnosis flow and use

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About this skill
What does the stata-environment-diagnose skill do?

Diagnose local Stata, MCP, package, startup, graph-export, and permissions issues. Use when setup is failing, Stata is not discovered, packages are missing, logs are truncated, or a managed machine behaves differently from a normal workstation.

How do I install it?

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