Updated 1mo ago
by Learning-Bayesian-Statistics
baygent-skills
A set of skills to call your agent Bayes. Thomas Bayes.
186 GitHub stars (186)
+3 in 16 days
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- 3 skills (3 skills found in its SKILL.md files)
- 19 forks (19 forks)
- 1mo ago last update (Last updated 1mo ago)
Install
Skills CLI
npx skills add Learning-Bayesian-Statistics/baygent-skills
Asks which skills and agents to install. Just one: npx skills add Learning-Bayesian-Statistics/baygent-skills --skill amortized-workflow — add -g for every project.
Claude Code
git clone https://github.com/Learning-Bayesian-Statistics/baygent-skillscp -r "baygent-skills/amortized-workflow" ~/.claude/skills/
Copies the amortized-workflow skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.
Plugin
/plugin marketplace add Learning-Bayesian-Statistics/baygent-skills
Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.
Skills can run code on your machine — read the SKILL.md first.
What it does
In the author's own words, from each skill's SKILL.md.
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amortized-workflow
Opinionated amortized Bayesian workflow with BayesFlow for simulation-based inference (SBI). Contains critical guardrails that agents will usually not apply unprompted — always consult before writing BayesFlow code. Trigger on: simulation-based inference, amortized inference, approximate Bayesian inference, BayesFlow, neural posterior estimation, posterior amortization, simulator design, prior de…
amortized-workflow/SKILL.md on GitHub (opens in a new tab) -
bayesian-workflow
Opinionated Bayesian modeling workflow with PyMC and ArviZ. Contains critical guardrails (nutpie sampler, prior/posterior predictive checks, LOO-PIT calibration, prior sensitivity checks, 94% HDI, non-centered parameterizations, reproducible seeds) that agents won't apply unprompted — always consult before writing Bayesian model code. Trigger on: building probabilistic/Bayesian models, prior elic…
bayesian-workflow/SKILL.md on GitHub (opens in a new tab) -
causal-inference
Production-grade Bayesian causal inference with PyMC, CausalPy, and DoWhy. Enforces DAG-first thinking, mandatory user checkpoints for assumptions, design-specific refutation, and defensible reporting with causal language guardrails. Trigger on: causal inference, causal effect estimation, treatment effects, counterfactuals, difference-in-differences (DiD), synthetic control, regression discontinu…
causal-inference/SKILL.md on GitHub (opens in a new tab)
No skill matches that filter.
Review before you install
A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.
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