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Updated a month ago

ai-ready

Vviktor-silakov
0.0k
viktor-silakov/ai-ready
86
Agent Score

💡 Summary

AI-ready skill analyzes repository readiness across eight key aspects and generates a phased improvement roadmap.

🎯 Target Audience

Software developers looking to improve code qualityProject managers assessing project readinessDevOps engineers optimizing workflowsTechnical leads ensuring best practicesQuality assurance teams focusing on documentation and testing

🤖 AI Roast: “Powerful, but the setup might scare off the impatient.”

Security AnalysisMedium Risk

Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); filesystem read/write scope and path traversal; dependency pinning and supply-chain risk. Run with least privilege and audit before enabling in production.

ai-ready-skill

A Claude Code skill for analyzing repository AI-readiness.

Scores 8 key aspects from 1-100 with ASCII progress bars, highlights problems by severity, and creates a phased refactoring roadmap.

╔══════════════════════════════════════════════════════════════════════╗
║                       AI-READINESS REPORT                            ║
║                       Repository: my-project                         ║
╠══════════════════════════════════════════════════════════════════════╣
║  OVERALL GRADE: B     SCORE: 76/100     ↑+12 from last run          ║
╠══════════════════════════════════════════════════════════════════════╣
║  1. Documentation       ████████░░ 82/100 ↑+5                        ║
║  2. Architecture        ███████░░░ 71/100 →0                         ║
║  3. Testing             ██████░░░░ 65/100 ↑+8                        ║
║  4. Type Safety         ████████░░ 84/100 ↑+2                        ║
║  5. Agent Instructions  █████░░░░░ 52/100 ↑+15                       ║
║  6. File Structure      ████████░░ 78/100 →0                         ║
║  7. Context Optimization██████░░░░ 63/100 ↑+3                        ║
║  8. Security            █████████░ 91/100 →0                         ║
╚══════════════════════════════════════════════════════════════════════╝

Features

  • 8 Aspect Analysis - Documentation, Architecture, Testing, Type Safety, Agent Instructions, File Structure, Context Optimization, Security
  • 95 Sub-criteria - Deep analysis with 10-15 checks per aspect
  • ASCII Dashboard - Visual progress bars and overall A-F grade
  • Severity Classification - Critical / Warning / Info issue grouping
  • Interactive Survey - Choose which issues to address
  • Phased Roadmap - Quick Wins → Foundation → Advanced
  • Template Generation - CLAUDE.md, ARCHITECTURE.md, llms.txt
  • Progress Tracking - Delta comparison between runs (↑+5, ↓-3)
  • Language Agnostic - Works with any programming language

Installation

Via skills.sh (recommended)

npx skills add viktor-silakov/ai-ready

skills.sh — universal skills manager for AI agents

Via npx

npx ai-ready-skill

Via npm

npm install -g ai-ready-skill
ai-ready-skill install

Usage

After installation, use in Claude Code:

# Analyze current directory
/ai-ready

# Analyze specific repository
/ai-ready /path/to/repo

CLI Commands

npx ai-ready-skill install   # Install skill (default)
npx ai-ready-skill check     # Check if installed
npx ai-ready-skill update    # Update to latest version
npx ai-ready-skill remove    # Remove skill
npx ai-ready-skill help      # Show help

Workflow

  1. Discovery - Detects language, framework, existing files
  2. Analysis - Evaluates all 8 aspects with sub-criteria
  3. Scoring - Calculates weighted scores and overall grade
  4. Dashboard - Displays ASCII progress bars
  5. Problems - Lists issues grouped by severity
  6. Survey - Asks which issues to fix (Critical=Y, others=N)
  7. Plan Mode - Creates phased implementation roadmap
  8. Templates - Generates missing files from templates
  9. Report - Saves AI-READINESS-REPORT.md with history

Aspects & Weights

| Aspect | Weight | Key Checks | |--------|--------|------------| | Documentation | 15% | README, JSDoc, ADRs, ARCHITECTURE.md | | Architecture | 15% | Modularity, boundaries, coupling, cohesion | | Testing | 12% | Coverage, co-location, naming, CI integration | | Type Safety | 12% | Strict mode, any usage, null safety | | Agent Instructions | 15% | CLAUDE.md completeness and quality | | File Structure | 10% | 150-500 LOC, nesting ≤5, files per dir ≤15 | | Context Optimization | 11% | llms.txt, chunking-friendly, why-comments | | Security | 10% | .aiignore, secrets, PII, NEVER rules |

Grade Scale

| Grade | Score | Description | |-------|-------|-------------| | A | 90-100 | Excellent - AI-ready | | B | 75-89 | Good - Minor improvements needed | | C | 60-74 | Moderate - Notable gaps | | D | 45-59 | Poor - Significant work needed | | F | 0-44 | Critical - Major overhaul required |

Severity Levels

Critical (blocks AI effectiveness)

  • Missing CLAUDE.md
  • Missing README.md
  • Files over 1000 LOC
  • Hardcoded secrets

Warning (impacts efficiency)

  • Files 500-1000 LOC
  • Missing ARCHITECTURE.md
  • Test coverage <50%
  • Deep nesting (>5 levels)

Info (optimization opportunities)

  • Files 400-500 LOC
  • Missing llms.txt
  • Minor documentation gaps

Generated Templates

The skill can generate these files:

  • CLAUDE.md - AI assistant guide with project context, commands, conventions, ALWAYS/NEVER rules
  • ARCHITECTURE.md - C4-style documentation with diagrams and design decisions
  • llms.txt - LLM-optimized project index for quick context loading

Output Files

After running, the skill creates:

your-repo/
└── AI-READINESS-REPORT.md    # Full report with history tracking

Requirements

License

MIT License - see LICENSE

Links

5-Dim Analysis
Clarity9/10
Novelty8/10
Utility9/10
Completeness9/10
Maintainability8/10
Pros & Cons

Pros

  • Comprehensive analysis of multiple aspects
  • Generates actionable improvement roadmap
  • Visual progress tracking with ASCII dashboard

Cons

  • Requires Node.js and Claude Code CLI
  • May need adjustments for specific languages
  • Dependency on external skills manager

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Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.

Copyright belongs to the original author viktor-silakov.