Borrowing it
Nothing to install: this file belongs to pymc-labs/decision-hub. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pymc-labs/decision-hub/main/CLAUDE.mdgit clone --depth 1 https://github.com/pymc-labs/decision-hubWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/pymc-labs/decision-hub/claude-md)<a href="https://agentmods.dev/instructions/pymc-labs/decision-hub/claude-md"><img src="https://agentmods.dev/badge/instructions/pymc-labs/decision-hub/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.04910 | $0.04910 |
| Opus 5 | $0.02455 | $0.02455 |
| Sonnet 5 | $0.00982 | $0.00982 |
| Haiku 4.5 | $0.00491 | $0.00491 |
Grade A, and why
decision-hub CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Overview
Workspace Structure
This is a uv workspace monorepo with four components:
client/—dhub-clipackage (open-source CLI, published to PyPI) — import path:dhub.*server/—decision-hub-serverpackage (private backend, deployed on Modal) — import path:decision_hub.*shared/—dhub-corepackage (shared domain models and SKILL.md manifest parsing) — import path:dhub_core.*frontend/— React + TypeScript web UI (bundled into the server at deploy time, not a uv workspace member)
shared/ is the single source of truth for data models (SkillManifest, RuntimeConfig, etc.) and manifest parsing. Both client and server depend on it — never duplicate these definitions.
Tech Stack
Backend (Python 3.11+):
- FastAPI for REST API (server)
- Typer + Rich for CLI (client)
- Pydantic for data validation and settings
- OpenRouter (Qwen) for LLM (gauntlet safety analysis, skill classification, search/ask, Cisco scanner — default backend, Gemini fallback)
- Gemini for embeddings (Gemini-only, no provider switch — stored vectors and query vectors must share one embedding space, so changing the embedding model is a migration requiring a full re-embed) and as fallback chat backend
- Anthropic for LLM (eval judging)
- boto3 for S3 access
- loguru for server logging
Frontend:
- React 19 with TypeScript
- Vite for bundling and dev server
- React Router for routing
Important: Always use uv run to execute Python code, not python directly.
Development Setup
Environments (Dev / Prod / Local)
The project has three environments controlled by DHUB_ENV (dev | prod | local). The server defaults to dev for safety; the CLI defaults to prod for end users.
Always work against dev unless explicitly told to use prod. Prefix all CLI, server, and deploy commands with DHUB_ENV=dev:
DHUB_ENV=dev dhub list # CLI against dev
DHUB_ENV=dev modal deploy modal_app.py # deploy dev Modal app (from server/)
DHUB_ENV=dev uv run --package decision-hub-server uvicorn ... # local dev server
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 270 lines · 4,910 tokens per session scan A 8a3bb3d7a4e2
decision-hub CLAUDE.md is an instructions file published in the GitHub repository pymc-labs/decision-hub (99 stars, last pushed 26d ago), licensed MIT. It adds 4,910 tokens to every session, about $0.0246 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.