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Generate and audit AI agent context files — tech debt scanner, GitHub health, cleanup agent

Project description

AnchorMD

Generate optimized CLAUDE.md files for AI coding agents in seconds.

Stop hand-rolling CLAUDE.md. Let Forge analyze your codebase and generate a production-grade configuration file that makes Claude Code, Cursor, Windsurf, and Codex actually understand your project.

Why?

AI coding agents are only as good as the context you give them. A well-crafted CLAUDE.md is the difference between an agent that writes idiomatic code and one that fights your conventions on every change.

AnchorMD:

  • Scans your codebase to detect languages, frameworks, and patterns
  • Generates a complete CLAUDE.md with coding standards, commands, and anti-patterns
  • Audits existing CLAUDE.md files and scores them against best practices
  • Framework-aware presets for React, FastAPI, Rust, Django, Next.js, and more

Install

pip install anchormd

Quick Start

# Generate a CLAUDE.md for your project
anchormd generate .

# Audit an existing CLAUDE.md
anchormd audit ./CLAUDE.md

# Interactive setup
anchormd init .

# See what would change
anchormd diff .

# List available presets
anchormd presets

# List framework-specific presets
anchormd frameworks

Example Output

Running anchormd generate . on a FastAPI project produces:

# CLAUDE.md — my-api

## Project Overview
my-api — TODO: Add project description.

## Current State
- **Version**: 0.1.0
- **Language**: Python
- **Files**: 47 across 2 languages
- **Lines**: 3,204

## Tech Stack
- **Language**: Python
- **Framework**: fastapi
- **Package Manager**: pip
- **Linters**: ruff
- **Test Frameworks**: pytest
- **CI/CD**: GitHub Actions

## Coding Standards
- **Naming**: snake_case
- **Type Hints**: present
- **Docstrings**: google style
- **Imports**: absolute

## Common Commands
...

## Anti-Patterns (Do NOT Do)
- Do NOT use synchronous database calls in async endpoints
- Do NOT return raw dicts — use Pydantic response models
- Do NOT use `os.path` — use `pathlib.Path` everywhere
...

GitHub Action

Add automated CLAUDE.md auditing to your CI pipeline:

# .github/workflows/claudemd-audit.yml
name: Audit CLAUDE.md
on: [pull_request]

jobs:
  audit:
    runs-on: ubuntu-latest
    permissions:
      pull-requests: write
    steps:
      - uses: actions/checkout@v6
      - uses: Arete-Consortium/anchormd@v0.1.0
        with:
          fail-below: 40     # Minimum passing score (0-100)
          comment: true       # Post results as PR comment

The action posts a formatted comment on your PR with score, findings, and recommendations.

Free vs Pro

Feature Free Pro ($8/mo)
generate — scan and produce CLAUDE.md Yes Yes
audit — score existing CLAUDE.md Yes Yes
11 community presets (FastAPI, React, Rust, Django...) Yes Yes
init — interactive guided setup - Yes
diff — detect drift between CLAUDE.md and codebase - Yes
CI integration — GitHub Action auto-audit on PR - Yes
6 premium presets (monorepo, data-science, devops...) - Yes
Team templates (shared org standards) - Planned

Get Pro: Monthly ($8/mo) | Yearly ($69/yr)

All 5 Tools Bundle: Monthly ($29/mo) | Yearly ($199/yr) — includes anchormd, agent-lint, ai-spend, promptctl, context-hygiene

Activate:

export ANCHORMD_LICENSE=ANMD-XXXX-XXXX-XXXX

Framework Presets

Preset Description
python-fastapi FastAPI + async patterns
python-cli Python CLI with typer/click
react-typescript React + TypeScript + hooks
nextjs Next.js App Router conventions
django Django with ORM patterns
rust Rust with clippy + proper error handling
go Go with standard project layout
node-express Express.js backend

Audit Scoring

Forge scores your CLAUDE.md on:

  • Section coverage — does it have the essentials?
  • Accuracy — does it match your actual codebase?
  • Specificity — are instructions actionable or vague?
  • Anti-patterns — does it prevent common mistakes?
  • Freshness — is it up to date?

Development

# Clone and install
git clone https://github.com/Arete-Consortium/anchormd.git
cd anchormd
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Lint
ruff check src/ tests/
ruff format src/ tests/

Community

Discord — Join the community

License

MIT

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Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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