AI Assistant Skill

AI Assistant Skill#

Bayesline ships a drift-resistant skill that teaches an AI coding assistant how to use the Bayesline Python API (bayesline.apiclient + bayesline.api) correctly — building risk models, uploading custom data, running reports, configuring portfolios, and explaining the engine’s math. It works with Claude Code and with Codex (and other AGENTS.md-based assistants).

The skill keeps API schemas and footguns as a single source of truth and points at the tutorial and recipe notebooks in this documentation for runnable, CI-tested worked examples — so it cannot silently drift from the real API.

Note

The skill bundle is available on request. Reach out to your Bayesline contact and we’ll provide it alongside your deployment.

Install#

First install the client and point it at your deployment:

pip install bayesline-apiclient
export BAYESLINE_ENDPOINT=https://your-deployment.example.com
export BAYESLINE_API_KEY=...        # omit for a local no-auth engine

Claude Code — unzip the bundle so it lives at .claude/skills/bayesline-api/ in your project (or under ~/.claude/skills/ to use it everywhere). Claude discovers it automatically via SKILL.md and loads reference files on demand.

Codex / other AGENTS.md assistants — place the unzipped folder in your project and make sure its AGENTS.md is discoverable (e.g. at the project root, or copy its contents into your existing AGENTS.md). These assistants have no skill auto-discovery, so AGENTS.md directs them to read reference/02-mental-model.md first.

What’s inside#

Path

Purpose

SKILL.md / AGENTS.md

Entry point + reference map (Claude / Codex)

reference/*.md

API schemas, idioms, footguns, and the math reference

notebooks/*.ipy

Runnable, CI-tested worked examples

notebook_env.py

Connection shim (reads BAYESLINE_ENDPOINT / BAYESLINE_API_KEY)

scripts/*.py

Copy-paste utilities (smoke test, dataset describe, tie-out)

The notebooks are the same ones rendered in the Tutorials and Recipes sections of these docs; open any of them and run the cells against your own deployment.