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Found 1,359 Skills
Use when conversation context is too long, hitting token limits, or responses are degrading. Compresses history while preserving critical information using anchored summarization and probe-based validation.
Data validation patterns including schema validation, input sanitization, output encoding, and type coercion. Use when implementing validate, validation, schema, form validation, API validation, JSON Schema, Zod, Pydantic, Joi, Yup, sanitize, sanitization, XSS prevention, injection prevention, escape, encode, whitelist, constraint checking, invariant validation, data pipeline validation, ML feature validation, or custom validators.
Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.
Generates CRUD REST API endpoints with request validation, TypeScript types, consistent response formats, error handling, and documentation. Includes route handlers, validation schemas (Zod/Joi), typed responses, and usage examples. Use when building "REST API", "CRUD endpoints", "API routes", or "backend endpoints".
End-to-end product development for iOS/macOS apps. Covers market research, competitive analysis, PRD generation, architecture specs, UX design, implementation guides, testing, and App Store release. Use for product planning, validation, or generating specification documents.
Debug FastAPI applications systematically with this comprehensive troubleshooting skill. Covers async/await issues, Pydantic validation errors (422 responses), dependency injection failures, CORS configuration problems, database session management, and circular import resolution. Provides structured four-phase debugging methodology with FastAPI-specific tools including uvicorn logging, OpenAPI docs, and middleware debugging patterns.
Manage terminology glossary with Vale. TRIGGERS - sync terms, glossary validation, add terms, Vale vocabulary.
Activated when the user wants to create a data model, validate data, serialize JSON, create Pydantic models, add validators, define settings, or create request/response schemas. Covers Pydantic v2 BaseModel, Field, validators, data validation, JSON schema generation, serialization, deserialization, and settings management.
Analyze propositions from multiple expert perspectives. Dynamically generates 4-6 relevant expert roles, then performs validation, comprehensive analysis, or debate-style examination. Use when user wants to examine ideas critically, find blindspots, or explore different viewpoints on a topic.
BDD-Driven Mathematical Content Verification Skill Combines Behavior-Driven Development with mathematical formula extraction, verification, and transformation using: - Cucumber/Gherkin for specification - RSpec for implementation verification - mathpix-gem for LaTeX/mathematical content extraction - Pattern matching on syntax trees for formula validation Enables iterative discovery and verification of mathematical properties through executable specifications.
Use when building secure AI pipelines or hardening LLM integrations. Defense-in-depth implements 8 validation layers from edge to storage with no single point of failure.
Generate structured agent prompts with FOCUS/EXCLUDE templates for task delegation. Use when breaking down complex tasks, launching parallel specialists, coordinating multiple agents, creating agent instructions, determining execution strategy, or preventing file path collisions. Handles task decomposition, parallel vs sequential logic, scope validation, and retry strategies.