Co-Pilot / 辅助式
更新于 a month ago

ai-ready

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

💡 摘要

AI准备技能分析存储库的准备情况,涵盖八个关键方面,并生成分阶段的改进路线图。

🎯 适合人群

希望提高代码质量的软件开发人员评估项目准备情况的项目经理优化工作流程的DevOps工程师确保最佳实践的技术负责人专注于文档和测试的质量保证团队

🤖 AI 吐槽:看起来很能打,但别让配置把人劝退。

安全分析中风险

风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发);文件读写范围与路径穿越风险;依赖锁定与供应链风险。以最小权限运行,并在生产环境启用前审计代码与依赖。

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

五维分析
清晰度9/10
创新性8/10
实用性9/10
完整性9/10
可维护性8/10
优缺点分析

优点

  • 对多个方面进行全面分析
  • 生成可操作的改进路线图
  • 使用ASCII仪表板进行可视化进度跟踪

缺点

  • 需要Node.js和Claude Code CLI
  • 可能需要针对特定语言进行调整
  • 依赖外部技能管理器

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 viktor-silakov.