Pydantic AI Agents

Build type-safe AI agents with Pydantic AI. Generates agent definitions with structured outputs, tool functions with dependency injection, streaming responses, and multi-agent orchestration patterns.

This skill helps you build production AI agents with Pydantic AI, the framework from the Pydantic team. It generates agent classes with system prompts and structured Pydantic outputs, defines tools with dependency injection for database and API access, implements streaming for real-time responses, creates multi-agent handoff patterns, and integrates with LangFuse for observability. Covers Logfire for debugging agent behavior.

When to use

Use when building AI agents with typed inputs/outputs, implementing tool-calling patterns, creating multi-agent systems, or integrating LLMs into Python applications with proper validation.

Examples

Customer support agent

Build an agent with tools for ticket lookup and refunds

Create a Pydantic AI agent for customer support with tools to look up orders, check refund eligibility, and process returns — with structured output for the response and action taken

Data extraction

Extract structured data from documents

Build a Pydantic AI agent that extracts invoice data (vendor, line items, totals, dates) from PDF text into a typed Pydantic model with validation