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PydanticAI & PydanticGraph — Type-Safe AI Agents & Graph Workflows
Build production-grade AI agents and graph-based state machines with PydanticAI and PydanticGraph. Agent creation, function tools, dependency injection, structured output, streaming, and graph control flow.
Why Install This Skill
When your agent loads this skill, it becomes a PydanticAI expert who can:
- Create type-safe agents — one-line agent creation with structured output validation
- Build function tools with dependencies — RunContext for dependency injection
- Stream outputs — text, events, and graph node streaming
- Use built-in capabilities — Thinking, WebSearch, MCP, Hooks, and 20+ more with on-demand loading
- Create graph state machines — PydanticGraph with BaseNode, GraphBuilder, parallel map/broadcast, joins with reducers
- Test systematically — TestModel, FunctionModel, Pydantic Evals
- Deploy to production — multi-agent patterns, MCP servers, durable execution
What You Get
| Directory | Purpose |
|---|---|
SKILL.md |
Quick reference, when-to-load table, common pattern gallery |
references/ |
8 reference files: core agents, capabilities/hooks, graph, models/output, patterns, testing/evals, examples, API reference, hybrid LangGraph patterns |
templates/ |
Runnable template implementations |
Triggers
Load this whenever building agents, tool-using LLM workflows, or graph-based state machines in Python.
Requirements
Python 3.10+ with pydantic-ai or pydantic-ai-slim package.
Quick Start
Start with the setup and first workflow in SKILL.md, then use the linked resources for the specific task you need to complete.