Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
8
Categories
9
Compatible tools
5
Contributors
1
8 skills
Plans and generates migration strategies for framework upgrades, language versions, database changes, and architecture shifts. Produces step-by-step migration guides with rollback plans, risk assessment, and automated codemods where possible.
Designs RESTful and GraphQL APIs following contract-first principles. Covers endpoint structure, request/response schemas, error handling, versioning, pagination, authentication, and rate limiting. Produces OpenAPI/Swagger specifications and implementation scaffolding.
Guides systematic code refactoring while preserving exact behavior. Identifies code smells, suggests appropriate refactoring patterns, and executes transformations incrementally with verification at each step. Follows Chesterton's Fence principle — understands why code exists before changing it.
Designs, optimizes, and iterates on prompts for LLM applications. Covers system prompt design, few-shot examples, chain-of-thought reasoning, output formatting, and prompt testing strategies. Helps build reliable AI-powered features.
Translates code between programming languages while preserving logic, idioms, and best practices of the target language. Handles differences in type systems, error handling, concurrency models, and standard library APIs. Produces idiomatic target code, not line-by-line transliteration.
Designs normalized database schemas from business requirements. Covers entity relationships, indexing strategies, migration planning, and performance considerations. Supports PostgreSQL, MySQL, MongoDB, and other databases with dialect-specific optimizations.
Performs comprehensive security analysis of code and configurations. Identifies OWASP Top 10 vulnerabilities, insecure patterns, missing input validation, authentication flaws, and secrets exposure. Provides remediation steps with secure code examples.
Identifies and resolves performance bottlenecks in code and systems. Covers algorithmic complexity analysis, memory optimization, caching strategies, database query tuning, and frontend performance (Core Web Vitals). Follows a measure-first approach.
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