AgentReady

import { Badge } from ‘@astrojs/starlight/components’;

AgentReady (v2.29.4) is a CLI tool that evaluates repositories for AI-assisted development readiness.

What it does

AgentReady scans a repository and scores it across 13 assessment categories:

• Documentation Standards
• Repository Structure
• Testing & CI/CD
• Security
• Context Window Optimization (includes CLAUDE.md presence and quality)
• Dependency Management
• CI/CD Integration
• Error Handling
• API Documentation
• Code Quality (includes complexity, type annotations, code smells)
• Git & Version Control
• Modularity
• Build & Development

Certification levels

Based on the overall score, repositories receive a certification:

Level	Score range	Meaning
Platinum	90—100	Fully optimized for AI-assisted development
Gold	75—89	Well prepared with minor gaps
Silver	60—74	Functional but could benefit from improvements
Bronze	Below 60	Significant preparation needed

Installation

# Using pip
pip install agentready

# Using uvx (no install needed)
uvx agentready

# Using a container
podman pull ghcr.io/ambient-code/agentready:latest

Usage

# Assess the current directory
agentready assess .

# Assess a specific repository
agentready assess /path/to/repo

# Output JSON report
agentready assess /path/to/repo --format json

# Generate markdown report (git-friendly)
agentready assess /path/to/repo --format markdown --output report.md

Output formats

• Interactive HTML — Opens in your browser with detailed breakdowns per category.
• Markdown — Git-friendly report suitable for committing to the repository.
• JSON — Machine-readable output for CI pipelines.

CI integration

Run AgentReady in CI to enforce a minimum readiness score:

- name: Check AI readiness
  run: |
    pip install agentready
    agentready assess . --format json --output report.json
    score=$(python -c "import json; print(json.load(open('report.json'))['score'])")
    if [ "$score" -lt 75 ]; then
      echo "AI readiness score $score is below threshold (75)"
      exit 1
    fi