Borrowing it
Nothing to install: this file belongs to tdi/awesome-private-ai. 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/tdi/awesome-private-ai/main/CLAUDE.mdgit clone --depth 1 https://github.com/tdi/awesome-private-aiWrote 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/tdi/awesome-private-ai/claude-md)<a href="https://agentmods.dev/instructions/tdi/awesome-private-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/tdi/awesome-private-ai/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/tdi/awesome-private-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/tdi/awesome-private-ai/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00493 | $0.00493 |
| Opus 5 | $0.00246 | $0.00246 |
| Sonnet 5 | $0.00099 | $0.00099 |
| Haiku 4.5 | $0.00049 | $0.00049 |
Grade A, and why
awesome-private-ai 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 9d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
This is Awesome Private AI - a curated list of tools, frameworks, and resources for running, building, and deploying AI privately (on-premises, air-gapped, or self-hosted). It's a community-maintained awesome list focused on privacy-first AI solutions.
Repository Structure
- README.md - Main curated list organized by categories (Inference Runtimes, Model Management, Fine-Tuning, etc.)
- CONTRIBUTING.md - Submission guidelines and requirements for new entries
- LICENSE - CC0-1.0 license
Content Categories
The list is organized into these main sections:
- Inference Runtimes & Backends
- Model Management & Serving
- Fine-Tuning & Adapters
- Vector Databases & Embeddings
- Agents & Orchestration
- VS Code Plugins & Extensions
- Privacy, Security & Governance
- Models for Private Deployment
- UI & Interaction Layers
- Datasets & Data Prep
- Learning Resources & Research
- AI Routers & API Aggregators
Contributing Guidelines
Submission Requirements
- Must support local model deployment - this is the core requirement
- Open-source projects strongly preferred
- Must be actively maintained (commits within last 6 months, 100+ GitHub stars)
- Clear documentation and installation instructions required
Entry Format
Follow this format: [Project Name](URL) - Brief description (max 2 lines).
Process
- Fork repository
- Add entry to appropriate category in alphabetical order
- Submit PR with title "Add [Project Name]"
- One project per pull request
What's Accepted
- Tools for on-premises/self-hosted AI model deployment
- Privacy-preserving AI solutions
- Air-gapped deployment tools
- Local inference frameworks
What's Rejected
- Cloud-only services without local deployment options
- Proprietary solutions without self-hosting capabilities
- Abandoned/unmaintained projects
Development Notes
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.
- 9d ago First seen · 65 lines · 493 tokens per session scan A aa64295379e5
awesome-private-ai CLAUDE.md is an instructions file published in the GitHub repository tdi/awesome-private-ai (186 stars, last pushed 6d ago), licensed CC0-1.0. It adds 493 tokens to every session, about $0.0025 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
awesome-ai-rules copilot-instructions.md
Copilot instructions for shumatsumonobu/awesome-ai-rules, covering copilot instructions, code style, database and don't.
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.