Transform legacy codebases into AI-ready projects by generating Claude Code configurations.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlegacy-to-ai-readyExecute the skills CLI command in your project's root directory to begin installation:
Fetches legacy-to-ai-ready from nicepkg/ai-workflow and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate legacy-to-ai-ready. Access via /legacy-to-ai-ready in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Transform legacy codebases into AI-ready projects by generating Claude Code configurations.
For most projects, start with just CLAUDE.md:
python scripts/analyze_codebase.py [path]Expand to full configuration only when needed.
Before generating configs, ask these questions:
Project Scope:
Pain Points:
Integration Needs:
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
| Config | Purpose | When to Create |
|---|---|---|
| CLAUDE.md | Project memory (shared) | Always (required) |
| CLAUDE.local.md | Personal preferences (git-ignored) | Individual customization |
| .claudeignore | Files Claude should not access | Sensitive files exist |
| .claude/rules/ | Path-specific rules | Multi-module projects |
| .claude/skills/ | Domain knowledge | Complex business logic |
| .claude/agents/ | Task specialists | Repeated review/debug tasks |
| .claude/commands/ | Quick prompts | Common workflows |
| .claude/settings.json | Hooks + permissions | Auto-formatting, security |
| MCP servers | External tools | Database/API integrations |
python scripts/analyze_codebase.py [project-path]
The script detects:
Output includes:
Claude should read:
Before creating custom configs, search for existing skills and MCP servers:
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.
Create at project root with:
See references/claude-md-patterns.md.
Create .claude/rules/ when:
See references/rules-patterns.md.
Create .claude/skills/ when:
See references/skills-patterns.md.
Create .claude/agents/ for:
See references/agents-patterns.md.
Create .claude/commands/ for:
See references/commands-patterns.md.
Configure .claude/settings.json for:
See references/hooks-patterns.md.
Configure MCP for:
See references/mcp-patterns.md.
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 | When to Read |
|---|---|
| examples.md | Complete real-world examples |
| resource-discovery.md | Find existing skills & MCP servers |
| advanced-patterns.md | Migrations, team collab, monorepos |
| claude-md-patterns.md | Creating CLAUDE.md |
| rules-patterns.md | Module-specific rules |
| skills-patterns.md | Domain knowledge |
| agents-patterns.md | Task specialists |
| commands-patterns.md | Quick prompts |
| hooks-patterns.md | Auto-formatting |
| mcp-patterns.md | External tools |
Templates:
assets/CLAUDE.md.template - Project memory templateassets/settings.json.template - Hooks configurationassets/claudeignore.template - File ignore patternsBundled skills to install in target project:
assets/skill-creator/ - For creating new project-specific skillsassets/skill-downloader/ - For downloading additional skillsassets/resource-scout/ - For discovering existing skills & MCP serversCopy 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:
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
davila7/claude-code-templates
intellectronica/agent-skills
am-will/codex-skills
sickn33/antigravity-awesome-skills
myzy-ai/dokie-ai-ppt
sickn33/antigravity-awesome-skills
legacy-to-ai-ready reduced setup friction for our internal harness; good balance of opinion and flexibility.
legacy-to-ai-ready reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added legacy-to-ai-ready from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend legacy-to-ai-ready for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend legacy-to-ai-ready for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: legacy-to-ai-ready is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in legacy-to-ai-ready — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
legacy-to-ai-ready is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in legacy-to-ai-ready — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: legacy-to-ai-ready is focused, and the summary matches what you get after install.
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