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bayesian-estimation

100 / 100 · Low risk

Fine to try.

By brycewang-stanford/Auto-Empirical-Research-Skills (GitHub) · research · 5,016 stars · scanned at commit 8684584

This skill covers Bayesian estimation and inference in quantitative social science. Use when the user is specifying priors, running MCMC, diagnosing chain convergence, or reporting posterior summaries — including hierarchical models, Bayesian structural models, and small-sample settings where priors regularize. Triggers on "Bayesian estimation", "Bayesian inference", "MCMC", "Markov chain Monte Carlo", "Stan", "PyMC", "NumPyro", "prior", "posterior", "credible interval", "Bayesian structural", …

Works with any agent that supports SKILL.md skills.

What this skill can do

We found nothing in the files we read that matches our rules. That does not prove the skill is safe: see the limits of static scanning.

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'bayesian-estimation' ] || [ -L ~/.agents/skills/'bayesian-estimation' ]; then echo 'A skill folder named bayesian-estimation already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills' "$d" && git -C "$d" checkout --quiet '8684584e7d1127940f018157d2c579974fae8f79' -- 'skills/11-James-Traina-compound-science/skills/bayesian-estimation' && mkdir -p ~/.agents/skills && cp -R "$d"/'skills/11-James-Traina-compound-science/skills/bayesian-estimation' ~/.agents/skills/'bayesian-estimation' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'bayesian-estimation' ~/.claude/skills/'bayesian-estimation' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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