Individual skill
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
cli-tool/components/skills/ai-research/pydantic-ai/SKILL.md
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- anthropic Repository topic
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# PydanticAI — Typed AI Agents in Python
## Overview
PydanticAI is a Python agent framework from the Pydantic team that brings the same type-safety and validation guarantees as Pydantic to LLM-based applications. It supports structured outputs (validated with Pydantic models), dependency injection for testability, streamed responses, multi-turn conversations, and tool use — across OpenAI, Anthropic, Google Gemini, Groq, Mistral, and Ollama. Use this skill when building production AI agents, chatbots, or LLM pipelines where correctness and testability matter.
## When to Use This Skill
- Use when building Python AI agents that call tools and return structured data
- Use when you need validated, typed LLM outputs (not raw strings)
- Use when you want to write unit tests for agent logic without hitting a real LLM
- Use when switching between LLM providers without rewriting agent code
- Use when the user asks about `Agent`, `@agent.tool`, `RunContext`, `ModelRetry`, or `result_type`
