Documentation

Make your codebase AI-ready with our suite of analysis tools

🚀 Quick Start

Get started in seconds with zero configuration:

# Run all tools at once
npx @aiready/cli scan ./src

Installation

You can use AIReady tools without installation via npx, or install globally for faster runs:

# Unified CLI (recommended)
npm install -g @aiready/cli
# Or install individual tools
npm install -g @aiready/pattern-detect
npm install -g @aiready/context-analyzer
npm install -g @aiready/consistency

Use with AI Agent

Prefer using AI agents like Cline, Cursor, or GitHub Copilot? Copy these ready-to-use prompts.

🔍 Basic Scan

agent prompt
Basic Scan Prompt

📊 Detailed Analysis

agent prompt
Detailed Analysis Prompt

Tools

🛡️

Pattern Detection

@aiready/pattern-detect

Find semantic duplicates that look different but do the same thing

✨ Features

  • ✓Semantic detection using Jaccard similarity on AST tokens
  • ✓Pattern classification (API handlers, validators, utilities)
  • ✓Token cost analysis showing wasted AI context budget
  • ✓Auto-excludes tests and build outputs
  • ✓Adaptive threshold based on codebase size

🚀 Quick Start

# Run without installation
npx @aiready/pattern-detect ./src

# Or use unified CLI
npx @aiready/cli scan ./src

📊 Example Output

📊 Duplicate Pattern Analysis
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📁 Files analyzed: 47
⚠️  Duplicate patterns: 12 files with 23 issues
💰 Wasted tokens: 8,450

CRITICAL (6 files)
  src/handlers/users.ts - 4 duplicates (1,200 tokens)
  src/handlers/posts.ts - 3 duplicates (950 tokens)

AI Readiness Scoring

📊 One Number, Complete Picture

Get a unified 0-100 score combining tools with proven default weights:

npx @aiready/cli scan ./src --score

Default Weights

  • Pattern Detection: 40%
  • Context Analysis: 35%
  • Consistency: 25%

Rating Scale

  • 90-100 Excellent
  • 75-89 Good
  • 60-74 Fair
  • 40-59 Needs Work
  • 0-39 Critical

🎯 Customizable Weights

Adjust weights to match your team's priorities:

# Prioritize pattern detection
aiready scan . --score --weights patterns:60,context:25,consistency:15
# Equal weighting
aiready scan . --score --weights patterns:33,context:33,consistency:34

Understanding Metrics

🧩 Knowledge Concentration

Measures "bus factor" for AI training. High concentration means AI only learns from one person's patterns.

65% Risk

📉 Tech Debt Interest

Calculates the "interest" paid every time an AI assistant uses a confusing pattern.

$1,240/mo waste

Measure what matters to your team

Need a custom metric for data quality, pipeline standards, or security?

Build New Metrics →

Unified CLI

Terminal — aiready scan

$ npx @aiready/cli scan ./src --score

🔍 Scanning 47 files...

🛡️ Pattern Detection: 85/100

📈 Context Analysis: 72/100

⚡ Consistency: 91/100

✨ AI Readiness Score: 82/100 (GOOD)

Need an Expert Audit?

While our tools give you the data, our experts provide the strategy. Get a comprehensive AI Readiness Audit for your enterprise codebase.

Professional AI Readiness Audit

Request a comprehensive strategy session and codebase audit for your team.

What you'll get:

  • ✓ Semantic duplicate report
  • ✓ Context window optimization
  • ✓ Naming consistency analysis
  • ✓ Actionable AI adoption roadmap

We'll never share your data. We'll email from the address on the site footer.

Prefer direct contact?

Email us: hello@getaiready.dev

CLI Options

--scoreCalculate AI Readiness Score
--jsonOutput report in JSON format
--includeGlob patterns to include
--excludeGlob patterns to exclude
--thresholdSet similarity threshold (0-1)
--verboseShow detailed output

Contributing

AIReady is open source. We welcome contributions to our analysis tools and core methodology. Want to build a new metric for your team?

View on GitHubBuild New Metrics