Stan Bayesian Modeling

SkillAI & models

Stan probabilistic programming for Bayesian inference

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Stan Bayesian Modeling skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/mathematics/skills/stan-bayesian-modeling/SKILL.md and read by ahel’s review.

Purpose

Provides Stan probabilistic programming capabilities for Bayesian inference and statistical modeling.

Capabilities

Stan model specification
MCMC sampling (NUTS, HMC)
Variational inference
Prior predictive checks
Posterior predictive checks
Model comparison (LOO-CV, WAIC)

Usage Guidelines

Model Specification: Write Stan code with clear blocks
Prior Selection: Choose appropriate, weakly informative priors
Diagnostics: Check Rhat, ESS, and divergences
Model Comparison: Use LOO-CV for model selection

Tools/Libraries

Stan
CmdStan
RStan
PyStan

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

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Item type: skill
Key: stan-bayesian-modeling
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter