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Found 105 Skills
Build Python APIs with FastAPI, Pydantic v2, and SQLAlchemy 2.0 async. Covers project structure, JWT auth, validation, and database integration with uv package manager. Prevents 7 documented errors. Use when: creating Python APIs, implementing JWT auth, or troubleshooting 422 validation, CORS, async blocking, form data, background tasks, or OpenAPI schema errors.
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke for async SQLAlchemy, JWT authentication, WebSockets, OpenAPI documentation.
Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
Build AI agents with Pydantic AI (Python) and Claude SDK (Node.js)
Generar modelos Pydantic a partir de OpenAPI/JSON Schema como fuente única de verdad
Expert guidance for SQLAlchemy 2.0 + Pydantic + PostgreSQL. Use when setting up database layers, defining models, creating migrations, or any database-related work. Automatically activated for DB tasks.
Define reusable Airflow task group templates with Pydantic validation and compose DAGs from YAML. Use when creating blueprint templates, composing DAGs from YAML, validating configurations, or enabling no-code DAG authoring for non-engineers.
This skill should be used when the user asks to "create api endpoint", "django ninja", "django api", "add endpoint", "rest api django", "ninja router", "api schemas", or mentions API development, endpoint organization, or Pydantic schemas in Django projects. Provides Django Ninja patterns with 1-endpoint-per-file organization.
Use when FastAPI validation with Pydantic models. Use when building type-safe APIs with robust request/response validation.
Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library
LangGraph state management patterns. Use when designing workflow state schemas, using TypedDict vs Pydantic, implementing accumulating state with Annotated operators, or managing shared state across nodes.