zjg540066169

AI4BayesCode

Build Bayesian MCMC samplers with AI4BayesCode — a header-only C++ library of composable, stateful block-wise MCMC kernels (Gibbs / NUTS / slice / ESS / VI / BART / GP / HMM / particle-Gibbs / RJMCMC / ...). Use when the user wants to (a) GENERATE a sampler for a Bayesian model by composing existing blocks, or (b) DESIGN a brand-new sampler block primitive for the library. Triggers: "I want a sampler for <model>", "compose / generate an MCMC sampler", "design a new block", a model written as y ~ ... with priors, or any AI4BayesCode request.

zjg540066169 0 Updated 2w ago

Resources

7
GitHub

Install

npx skillscat add zjg540066169/ai4bayescode

Install via the SkillsCat registry.

SKILL.md

AI4BayesCode

You are launching AI4BayesCode — a stateful, block-wise MCMC sampler system. Your job is to
either compose an existing-block sampler for the user's model (the codegen flow) or design a
brand-new block primitive for the library (the block_design flow).

Bootstrap — do this FIRST

Read start.md at this skill's root. It is the canonical entry point / router; follow it
exactly:

  • it routes the request into the codegen flow (compose existing blocks for a model the user
    describes) or the block_design flow (design a new primitive);
  • it carries the phase schedule, the lazy-load rule, the structured-question protocol, and the
    per-phase sign-off gates.

Do NOT restate or duplicate start.md here — READ it, then follow it.

Token discipline (lazy-load)

Read start.md first. Then load each sub-skill ONLY when you enter that phase —
skills/codegen.md, skills/block_design_skills/00_flow.md, the skills/system_design_skills/
modules, etc. NEVER preload the whole skills/ tree. If unsure whether you need a module yet, do
not load it.

The library lives HERE

This skill bundles the AI4BayesCode C++ library, not just the guidance:

  • the built-in block headers + system dependencies are under include/ at this skill's
    root; the routing index of built-in blocks is skills/block_catalogue/index.md; reference
    examples are in examples/.
  • The AI4BayesCode library root IS this skill's directory (where this SKILL.md / start.md
    live). Treat it as the RESOLVED AI4BayesCode path for the whole session: the codegen flow does
    NOT ask "Path to the AI4BayesCode folder" — use this skill root automatically, and substitute
    its absolute path for the bare AI4BayesCode/ prefix in every compile recipe (so the -I points
    at <this-skill>/include). Only ask for a path if the user explicitly wants a DIFFERENT
    AI4BayesCode checkout.
  • User-GENERATED output (the new .cpp + runner, or a new blocks_local/<Block>/ bundle)
    goes in the USER's own project (./generated/..., the user's chosen folder), NEVER inside
    this installed skill directory.

Install / update

See AI_AGENT_INSTALL.md for the agent-driven install runbook (Claude Code / Codex / Cursor).
After install, reload the agent; then typing /AI4BayesCode loads this skill (which bootstraps
start.md).

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