Getting Started with AIReady CLI: Make Your Codebase AI-Ready in 5 Minutes

Have you ever noticed that AI coding assistants sometimes give you worse suggestions over time? Or that they keep suggesting code that already exists in your project? You're not alone — and there's a tool that can help.

AIReady is an open-source CLI that analyzes your codebase and tells you exactly where AI tools struggle — and how to fix it. In this guide, you'll learn how to scan your codebase, understand your AI readiness score, and start improving in just 5 minutes.

What You'll Learn

• How to install AIReady CLI
• How to scan your codebase
• How to understand your AI readiness score
• How to fix common issues
• How to track improvements over time

Prerequisites

• Node.js 18 or higher
• A codebase to analyze (any TypeScript, JavaScript, Python, Java, Go, or C# project)

Step 1: Install AIReady CLI

# Install globally
npm install -g @aiready/cli

# Or use npx without installing
npx @aiready/cli scan .

Step 2: Scan Your Codebase

Navigate to your project directory and run:

# Scan current directory
aiready scan .

# Or scan a specific directory
aiready scan ./src

You'll see output like this:

🎯 AI Readiness Score: 72/100 (Fair)

📊 Breakdown:
  • Pattern Detection:    65/100  (12 semantic duplicates found)
  • Context Analysis:     78/100  (Import depth: 4 levels)
  • Consistency:          82/100  (Naming conventions: 90% consistent)
  • Contract Enforcement: 70/100  (Type safety: Good)
  • Documentation:        68/100  (3 outdated docs found)

💡 Top Recommendations:
  1. Consolidate 12 similar validation functions
  2. Reduce import chain depth from 4 to 3 levels
  3. Update 3 documentation files that are out of sync

Step 3: Understand Your Score

Your AI readiness score (0-100) tells you how well AI tools will work with your codebase:

Step 4: Fix Common Issues

Issue 1: Semantic Duplicates

AI tools can't see that similar functions do the same thing. AIReady finds them:

# Find semantic duplicates
aiready patterns . --similarity 0.7

Fix: Consolidate similar functions into a single, well-documented utility.

Issue 2: Deep Import Chains

When imports are 5+ levels deep, AI tools lose context:

# Analyze import depth
aiready context . --max-depth 3

Fix: Flatten your module structure or use barrel exports.

Issue 3: Inconsistent Naming

AI tools learn from your patterns. Inconsistent naming confuses them:

# Check naming consistency
aiready consistency .

Fix: Standardize naming conventions across your codebase.

Step 5: Track Improvements

Save Your Results

# Save results to JSON
aiready scan . --output json

# Results are saved to .aiready/ directory

Visualize Your Codebase

# Generate interactive visualization
aiready visualise .

# Opens a force-directed graph showing relationships

Upload to Platform (Optional)

# Create a free account at platform.getaiready.dev
# Then upload your results
aiready scan . --upload --api-key ar_your_key

Track trends over time and see your improvements!

Step 6: Integrate into Your Workflow

Add to CI/CD

# GitHub Actions example
- name: Check AI Readiness
  run: |
    npx @aiready/cli scan . --score --threshold 75

Pre-commit Hook

// Add to package.json
{
  "scripts": {
    "precommit": "aiready scan . --score --threshold 70"
  }
}

VS Code Extension

Install the AIReady VS Code extension for real-time feedback as you code.

Real-World Example

Let's see how AIReady helped improve a real project:

Before:

• Score: 62/100
• 23 semantic duplicates
• Import depth: 5 levels
• 8 inconsistent naming patterns

After 2 hours of fixes:

• Score: 84/100
• 3 semantic duplicates (87% reduction)
• Import depth: 3 levels
• 1 inconsistent pattern (88% improvement)

Result: AI coding assistants now give relevant suggestions 40% faster.

Next Steps

1. Join the community: Discord
2. Track trends: Platform
3. Read more: AI Engineering Handbook
4. Contribute: GitHub

Common Questions

Q: Does AIReady work with my framework?

A: Yes! AIReady supports TypeScript, JavaScript, Python, Java, Go, and C#. It works with any framework.

Q: Is it free?

A: Yes! The CLI and all analysis tools are free and open source. The Platform has a free tier with paid plans for teams.

Q: How is this different from a linter?

A: Linters check code quality for humans. AIReady checks code quality for AI tools. They're complementary, not competing.

Q: Can I use this in my company?

A: Absolutely! AIReady is MIT licensed. Use it anywhere.

Conclusion

Making your codebase AI-ready isn't about perfection — it's about removing the friction that makes AI tools less effective. Start with a scan, fix the top 3 issues, and watch your AI assistants become more helpful.

Ready to try it? Run this now:

npx @aiready/cli scan .

Found this helpful? Share it with your team and join our Discord community to discuss AI readiness strategies.

Want to track improvements over time? Check out AIReady Platform for trend tracking, team collaboration, and CI/CD integration.