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legacy-to-ai-ready

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Legacy to AI-Ready

Transform legacy codebases into AI-ready projects by generating Claude Code configurations.

Quick Start (5-Minute Setup)

For most projects, start with just CLAUDE.md:

  1. Analyze: python scripts/analyze_codebase.py [path]
  2. Create CLAUDE.md with build commands, code style, architecture overview
  3. Done - Claude can now write code following your project's conventions

Expand to full configuration only when needed.

Interactive Discovery

Before generating configs, ask these questions:

Project Scope:

  • What is this project? (web app, API, CLI, library)
  • Primary language and frameworks?
  • Team size? (solo, small team, enterprise)

Pain Points:

  • What mistakes do new developers commonly make?
  • What patterns should always be followed?
  • What operations are repeated frequently?

Integration Needs:

  • External services used? (databases, APIs, cloud)
  • CI/CD pipeline? (GitHub Actions, Jenkins)
  • Code quality tools? (linters, formatters)

Configuration Decision Tree

Start
│
├─ Small project / Solo dev
│  └─ CLAUDE.md only
│
├─ Team project
│  ├─ Multi-language? → Add .claude/rules/
│  ├─ Complex domain? → Add .claude/skills/
│  ├─ Code reviews? → Add .claude/agents/
│  └─ Repeated tasks? → Add .claude/commands/
│
└─ Enterprise / Large team
   └─ All configurations + MCP servers + Hooks

Generated Configurations

ConfigPurposeWhen to Create
CLAUDE.mdProject memory (shared)Always (required)
CLAUDE.local.mdPersonal preferences (git-ignored)Individual customization
.claudeignoreFiles Claude should not accessSensitive files exist
.claude/rules/Path-specific rulesMulti-module projects
.claude/skills/Domain knowledgeComplex business logic
.claude/agents/Task specialistsRepeated review/debug tasks
.claude/commands/Quick promptsCommon workflows
.claude/settings.jsonHooks + permissionsAuto-formatting, security
MCP serversExternal toolsDatabase/API integrations

Workflow

Phase 1: Automated Analysis

python scripts/analyze_codebase.py [project-path]

The script detects:

  • Languages and frameworks
  • Directory structure patterns
  • Development tools (linters, formatters)
  • Git commit patterns
  • Environment variables
  • Code style indicators
  • CI/CD configurations (GitHub Actions, etc.)
  • Sensitive files (warns about .env, credentials)

Output includes:

  • Recommendations for which configs to create
  • Security warnings for sensitive files
  • Suggested .claudeignore patterns

Phase 2: Context Gathering

Claude should read:

  1. 3-5 representative source files - understand naming, patterns
  2. Test files - understand testing approach
  3. Config files - package.json, tsconfig, etc.
  4. README/docs - project overview
  5. Recent commits - understand commit style

Phase 2.5: Discover Existing Resources

Before creating custom configs, search for existing skills and MCP servers:

  1. Search skill marketplaces - SkillsMP, SkillHub.club, Claude Skills Hub
  2. Check GitHub repositories - awesome-claude-skills, themed skill collections
  3. Find relevant MCP servers - Glama, MCP Market, official registry

See references/resource-discovery.md for complete directory of sources.

Tip: Many common needs (git commit, code review, database patterns) already have well-maintained skills available.

Phase 3: Generate Configurations

1. CLAUDE.md (Required)

Create at project root with:

  • Quick reference commands (build, test, lint)
  • Naming conventions
  • Architecture overview
  • Testing guidelines
  • Git workflow

See references/claude-md-patterns.md.

2. Rules (If Multi-Module)

Create .claude/rules/ when:

  • Multiple languages need different conventions
  • Modules have distinct patterns (frontend/backend)
  • Path-specific requirements exist

See references/rules-patterns.md.

3. Skills (If Complex Domain)

Create .claude/skills/ when:

  • Domain-specific workflows exist (database, API patterns)
  • Team knowledge needs preservation
  • Complex procedures are repeated

See references/skills-patterns.md.

4. Subagents (If Specialized Tasks)

Create .claude/agents/ for:

  • Code review automation
  • Debugging assistance
  • Security auditing
  • Documentation generation

See references/agents-patterns.md.

5. Commands (If Common Operations)

Create .claude/commands/ for:

  • Git commit workflow
  • PR review process
  • Deployment steps
  • Test running

See references/commands-patterns.md.

6. Hooks (If Auto-Formatting Needed)

Configure .claude/settings.json for:

  • Auto-format on file edit
  • Protected files
  • Command logging

See references/hooks-patterns.md.

7. MCP Servers (If External Integrations)

Configure MCP for:

  • Database access
  • GitHub integration
  • Slack notifications
  • Custom internal tools

See references/mcp-patterns.md.

Phase 4: Validate

  1. Ask Claude to perform a typical task
  2. Verify it follows project conventions
  3. Iterate based on gaps discovered

Output Structure

Minimal (small projects):

project/
├── CLAUDE.md
└── [existing files]

Standard (team projects):

project/
├── CLAUDE.md
├── .claude/
│   ├── rules/
│   │   └── code-style.md
│   └── commands/
│       └── commit.md
└── [existing files]

Complete (enterprise):

project/
├── CLAUDE.md              # Shared project memory
├── CLAUDE.local.md        # Personal (git-ignored)
├── .claudeignore          # Files to protect
├── .claude/
│   ├── settings.json      # Hooks + permissions
│   ├── rules/
│   ├── skills/
│   ├── agents/
│   └── commands/
└── [existing files]

Reference Materials

ReferenceWhen to Read
examples.mdComplete real-world examples
resource-discovery.mdFind existing skills & MCP servers
advanced-patterns.mdMigrations, team collab, monorepos
claude-md-patterns.mdCreating CLAUDE.md
rules-patterns.mdModule-specific rules
skills-patterns.mdDomain knowledge
agents-patterns.mdTask specialists
commands-patterns.mdQuick prompts
hooks-patterns.mdAuto-formatting
mcp-patterns.mdExternal tools

Templates & Bundled Skills

Templates:

  • assets/CLAUDE.md.template - Project memory template
  • assets/settings.json.template - Hooks configuration
  • assets/claudeignore.template - File ignore patterns

Bundled skills to install in target project:

  • assets/skill-creator/ - For creating new project-specific skills
  • assets/skill-downloader/ - For downloading additional skills
  • assets/resource-scout/ - For discovering existing skills & MCP servers

Installing Bundled Skills

Copy these skills to the target project's .claude/skills/ directory:

cp -r assets/skill-creator [target-project]/.claude/skills/
cp -r assets/skill-downloader [target-project]/.claude/skills/
cp -r assets/resource-scout [target-project]/.claude/skills/

This enables the target project to:

  1. resource-scout - Discover existing skills & MCP servers before building custom
  2. skill-downloader - Download and install skills from GitHub or archives
  3. skill-creator - Create custom skills tailored to their domain

Language Quick Reference

TypeScript/JavaScript

  • Extract: eslint, prettier, tsconfig
  • Hooks: prettier auto-format
  • Skills: API patterns, component patterns

Python

  • Extract: black, ruff, mypy, pyproject.toml
  • Hooks: black/ruff auto-format
  • Skills: API patterns, ORM patterns

Go

  • Extract: gofmt, golangci-lint
  • Hooks: gofmt auto-format
  • Skills: error handling patterns

Rust

  • Extract: rustfmt, clippy
  • Hooks: rustfmt auto-format
  • Skills: error handling, async patterns

Source

git clone https://github.com/nicepkg/ai-workflow/blob/main/.claude/skills/legacy-to-ai-ready/SKILL.mdView on GitHub

Overview

Legacy to AI-Ready helps you convert aging codebases into Claude Code configurations. Start with CLAUDE.md to establish project memory, build commands, and coding conventions, then expand to .claude/skills, .claude/agents, and more as needed. This approach supports AI-assisted development and streamlined onboarding.

How This Skill Works

Run automated analysis with analyze_codebase.py to identify languages, structure, tools, and sensitive files. The tool outputs recommendations and security notes, then you create CLAUDE.md and progressively add modules like .claude/skills, .claude/rules, and .claude/agents. This enables Claude Code to follow project conventions and scale across teams.

When to Use It

  • Analyzing old projects to generate AI coding configurations
  • Creating CLAUDE.md, skills, subagents, slash commands, hooks, or rules for existing projects
  • User wants vibe coding for a codebase
  • Onboarding new team members with AI-assisted development
  • User mentions make project AI-ready, generate Claude config, or create coding standards for AI

Quick Start

  1. Step 1: Analyze: python scripts/analyze_codebase.py [path]
  2. Step 2: Create CLAUDE.md with build commands, code style, architecture overview
  3. Step 3: Done - Claude can now write code following your project's conventions

Best Practices

  • Start with CLAUDE.md before expanding to full configurations to establish a single source of truth
  • Run analyze_codebase.py to generate concrete config recommendations and security notes
  • Capture 3-5 representative source files, tests, and key config files for accurate context
  • Organize Claude artifacts by purpose: skills, agents, commands, and rules in .claude/*
  • Regularly review and update CLAUDE.md, .claude/settings.json, and related configs as the project evolves

Example Use Cases

  • A legacy web app is analyzed to generate CLAUDE.md and initial rules for consistent coding practices
  • A multi-language monorepo is extended with .claude/skills and .claude/agents to handle complex workflows
  • Vibe coding is enabled in a codebase to enforce stylistic and behavioral conventions with Claude
  • New backend developers are onboarded using AI-assisted development prompts and project memory
  • AI-ready standards are created to guide CI/CD, testing, and environment handling across teams

Frequently Asked Questions

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