Package Exports
- @aiready/cli
Readme
@aiready/cli
Assess and improve your codebase's AI-readiness. Get an AI Readiness Score (0-100) and detect issues that confuse AI models.
🚀 Quick Start
# Install globally
npm install -g @aiready/cli
# Scan your codebase
aiready scan .
# Get detailed analysis
aiready scan . --output report.json🤖 Why AIReady?
As AI becomes deeply integrated into software development, codebases become harder for AI models to understand due to:
- Knowledge cutoff limitations in AI models
- Context fragmentation that breaks AI understanding
- Duplicated patterns AI doesn't recognize
- Inconsistent naming across the codebase
AIReady helps teams assess, visualize, and prepare repositories for better AI adoption.
🌟 The AIReady Ecosystem
| Integration | Package | Description |
|---|---|---|
| CLI | @aiready/cli |
Unified command-line interface |
| VS Code | aiready |
Real-time AI readiness analysis in VS Code |
| GitHub Action | aiready-action |
CI/CD integration for automated scans |
| MCP Server | @aiready/mcp-server |
Model Context Protocol server for AI assistants |
| Skills | @aiready/skills |
AI-friendly coding practices for agents |
| Docker | aiready/cli |
Containerized CLI |
| Homebrew | brew install caopengau/aiready/aiready |
macOS package |
✨ Features
- AI Readiness Score - Get a 0-100 score indicating how AI-ready your codebase is
- Semantic Duplicate Detection - Find duplicate patterns that waste AI context window tokens
- Context Analysis - Analyze context window costs, import depth, and dependency fragmentation
- Consistency Checks - Ensure naming conventions and pattern consistency
- Documentation Drift - Track documentation freshness vs code churn
- Testability Assessment - Measure code testability for AI agents
- Agent Grounding - Evaluate how well code aids AI agents
- Contract Enforcement - Measure structural type safety and boundary validation
- Interactive Visualization - Generate force-directed graph visualizations
- CI/CD Integration - Quality gates for AI readiness in your pipeline
📋 Commands
Unified Scan
Run all analysis tools at once:
aiready scan .
aiready scan . --output report.json
aiready scan . --threshold 70Individual Tools
| Command | Description |
|---|---|
aiready patterns |
Detect semantic duplicates and patterns |
aiready context |
Analyze context window cost & dependencies |
aiready consistency |
Check naming conventions |
aiready testability |
Assess code testability |
aiready contract |
Analyze structural type safety & contracts |
aiready visualize |
Generate interactive visualizations |
aiready upload |
Upload results to AIReady platform |
📦 Installation
npm / pnpm / yarn
# npm
npm install -g @aiready/cli
# pnpm
pnpm add -g @aiready/cli
# yarn
yarn global add @aiready/cliDocker
# Pull from Docker Hub
docker pull aiready/cli
# Run
docker run aiready/cli scan .
# Or use the image directly
docker run -v $(pwd):/app aiready/cli scan /appHomebrew
brew install caopengau/aiready/aireadyVS Code Extension
Install from VS Code Marketplace or search for "AIReady" in VS Code extensions.
GitHub Action
- name: AIReady Code Analysis
uses: caopengau/aiready-action@v1
with:
threshold: 70MCP Server
npm install -g @aiready/mcp-server
aiready-mcp🔧 Configuration
Create an aiready.json config file:
{
"scan": {
"exclude": ["**/dist/**", "**/node_modules/**"]
},
"tools": {
"pattern-detect": { "minSimilarity": 0.5 },
"context-analyzer": { "maxContextBudget": 15000 }
},
"output": { "format": "json", "directory": ".aiready" }
}🌐 Language Support
Currently Supported (95% market coverage):
- ✅ TypeScript / JavaScript
- ✅ Python
- ✅ Java
- ✅ Go
- ✅ C#
🏗️ Architecture
🎯 USER
│
▼
🎛️ @aiready/cli (orchestrator)
│ │ │ │ │ │ │ │ │ │
▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼
[PAT] [CTX] [CON] [AMP] [DEP] [DOC] [SIG] [AGT] [TST] [CTR]
│ │ │ │ │ │ │ │ │ │
└─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┘
│
▼
🏢 @aiready/core🤝 Contributing
See CONTRIBUTING.md for details.
📄 License
MIT License - see LICENSE for details.
🔗 Related Links
- 🌐 Website
- 📖 Documentation
- 📦 npm
- 📊 GitHub Actions
- 🔌 VS Code Extension