Assess and improve your codebase's AI-readiness. Get an AI Readiness Score (0-100) and detect issues that confuse AI models.
# Install globally
npm install -g @aiready/cli
# Scan your codebase
aiready scan .
# Get detailed analysis
aiready scan . --output report.jsonAs 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.
| Integration | Package | Description |
|---|---|---|
| CLI | @aiready/cli |
Unified command-line interface |
| MCP Server | @aiready/mcp-server |
Cursor-Ready: Bridge AI agents to the Platform Swarm |
| Remediation Swarm | Platform | AI-to-AI Fixes: Automated refactors via specialized agents |
| GitHub Action | aiready-action |
No-Regression: CI/CD gate for AI leverage |
| VS Code | aiready |
Real-time AI readiness analysis in VS Code |
- AI Readiness Score - Get a 0-100 score indicating how AI-ready your codebase is.
- π‘οΈ AI-Regression Guardrail - Block PRs that reduce your AI leverage (GitHub Action).
- π€ Remediation Swarm - Automatically fix AI-readiness issues using the platform's specialized agents.
- π Cursor-Ready MCP Server - Let your AI assistant (Cursor, Windsurf, Claude) find and remediate code issues directly in your IDE.
- 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.
- Agent Grounding - Evaluate how well code aids AI agents and autonomous workflows.
Run all analysis tools at once:
aiready scan .
aiready scan . --output report.json
aiready scan . --threshold 70See suggested fixes for detected issues:
aiready remediate # Show remediation options for latest report
aiready remediate --tool patterns # Focus on pattern consolidation fixesNote: Advanced automated remediation requires an AIReady Platform subscription and an API key.
| 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 |
# npm
npm install -g @aiready/cli
# pnpm
pnpm add -g @aiready/cli
# yarn
yarn global add @aiready/cli# 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 /appbrew install getaiready/aiready/aireadyInstall from VS Code Marketplace or search for "AIReady" in VS Code extensions.
- name: AIReady Code Analysis
uses: getaiready/aiready-action@v1
with:
threshold: 70npm install -g @aiready/mcp-server
aiready-mcpCreate 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" }
}Currently Supported (95% market coverage):
- β TypeScript / JavaScript
- β Python
- β Java
- β Go
- β C#
π― USER
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π’ @aiready/core
See CONTRIBUTING.md for details.
MIT License - see LICENSE for details.
- π Website
- π Documentation
- π¦ npm
- π GitHub Actions
- π VS Code Extension