pymc-bayesian-modeling
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
npx skills add foryourhealth111-pixel/Vibe-Skills --skill pymc --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# PyMC Bayesian Modeling ## Routing Boundary Use this skill only for PyMC, probabilistic programming, Bayesian hierarchical models, NUTS/MCMC sampling, posterior predictive checks, and PyMC model diagnostics. Do not use it for generic regression, scikit-learn modeling, causal analysis, pymoo optimization, or materials-science prompts. ## Overview PyMC is a Python library for Bayesian modeling and
What does the pymc-bayesian-modeling skill do?
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
How do I install it?
Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill pymc --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 foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 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.