Skills

Designs and scaffolds AI agent architectures including tool definitions, system prompts, memory strategies, and orchestration logic. Supports multi-agent workflows, ReAct patterns, function calling schemas, and MCP server configurations. Helps structure agents that are reliable, observable, and easy to debug.

Generates type-safe API client SDKs from OpenAPI specs, API documentation, or example requests. Produces clean, well-typed client code with error handling, retry logic, pagination helpers, and authentication setup. Supports TypeScript, Python, Go, and Rust.

Helps architect scalable distributed systems by analyzing requirements and producing high-level architecture diagrams, component breakdowns, data flow descriptions, and technology recommendations. Covers load balancing, caching strategies, database selection, message queues, and failure handling patterns.

Analyzes and resolves git merge conflicts by understanding the intent of both sides. Examines the conflict markers, surrounding context, and commit history to produce a correct merged result that preserves both changes without breaking functionality.

Generates TypeScript type definitions from various sources — JSON data, API responses, database schemas, or plain descriptions. Produces strict types with proper generics, utility types, discriminated unions, and JSDoc comments.

Designs and implements comprehensive error handling for APIs. Covers error response formats (RFC 7807 Problem Details), HTTP status code selection, error logging strategies, retry logic, and client-friendly error messages with proper i18n support.

Generates complete OpenAPI 3.1 specifications from API descriptions, existing code, or route definitions. Includes request/response schemas, authentication, error responses, examples, and server configurations. Produces valid YAML ready for Swagger UI.

Generates production-ready React components with TypeScript, proper props interfaces, accessibility attributes, responsive design, and test files. Follows modern patterns including Server Components, Suspense boundaries, and composition over inheritance.

Explains complex code in plain language at the requested level of detail. Breaks down algorithms, design patterns, and architecture decisions. Adapts explanation depth from high-level overview to line-by-line walkthrough based on audience.

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.

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.

Builds, explains, and tests regular expressions from natural language descriptions. Supports multiple regex flavors (PCRE, JavaScript, Python, Go). Provides step-by-step breakdowns, test cases, and performance considerations for complex patterns.

Systematic debugging workflow that helps identify, isolate, and fix bugs. Follows a structured approach: reproduce, localize, reduce, fix, guard. Analyzes error messages, stack traces, and logs to pinpoint root causes rather than symptoms.

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.

Automated code review that provides actionable feedback on code quality, potential bugs, performance issues, security vulnerabilities, and style violations. Analyzes code changes with the rigor of a senior engineer, providing specific suggestions with code examples.