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Found 81 Skills
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.
Build conversational AI agents using Pydantic AI + OpenRouter. Use when creating type-safe Python agents with tool calling, validation, and streaming.
Professional Pydantic v2.12 development for data validation, serialization, and type-safe models. Use when working with Pydantic for (1) creating or modifying BaseModel classes, (2) implementing validators and serializers, (3) configuring model behavior, (4) handling JSON schema generation, (5) working with settings management, (6) debugging validation errors, (7) integrating with ORMs or APIs, or (8) any production-grade Python data validation tasks. Includes complete API reference, concept guides, examples, and migration patterns.
Converts JSON data snippets into Python Pydantic data models.
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
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.
Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke for async SQLAlchemy, JWT authentication, WebSockets, OpenAPI documentation.
FastAPI best practices and conventions. Use when working with FastAPI APIs and Pydantic models for them. Keeps FastAPI code clean and up to date with the latest features and patterns, updated with new versions. Write new code or refactor and update old code.
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
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
Build AI agents with Pydantic AI (Python) and Claude SDK (Node.js)