dougtrajano/pydantic-ai-skills/pydanticai-docs

Pydantic AI Documentation Skill

What is Pydantic AI?

Pydantic AI is a production-grade Python agent framework for building type-safe, dependency-injected Generative AI applications. It supports multiple LLM providers, structured outputs via Pydantic models, and composable multi-agent patterns.

Doc: <https://ai.pydantic.dev/>

Core Concepts

1. Agent Instantiation

from pydantic_ai import Agent
agent = Agent(
    'openai:gpt-4o',          # model string: provider:model-name
    system_prompt='Be helpful.',
)
result = agent.run_sync('What is the capital of France?')
print(result.output)

For full constructor parameters, run methods, and streaming: load references/AGENT.md.

2. Function Tools (@agent.tool)

from pydantic_ai import Agent, RunContext
agent = Agent('openai:gpt-4o', deps_type=str)
@agent.tool
def get_user_name(ctx: RunContext[str]) -> str:
    """Return the current user's name."""
    return ctx.deps
result = agent.run_sync('What is my name?', deps='Alice')

Use @agent.tool_plain when you don't need RunContext. For tool registration, return types, and retries: load references/FUNCTION_TOOLS.md.

3. Dependency Injection (RunContext)

from dataclasses import dataclass
from pydantic_ai import Agent, RunContext
@dataclass
class MyDeps:
    api_key: str
    user_id: int
agent = Agent('openai:gpt-4o', deps_type=MyDeps)
@agent.tool
async def fetch_data(ctx: RunContext[MyDeps]) -> str:
    return f'User {ctx.deps.user_id}'

For RunContext fields, injection into system prompts and output validators: load references/DEPENDENCIES.md.

4. Structured Output

from pydantic import BaseModel
from pydantic_ai import Agent
class CityInfo(BaseModel):
    city: str
    country: str
agent = Agent('openai:gpt-4o', output_type=CityInfo)
result = agent.run_sync('Where were the 2012 Olympics held?')
print(result.output)  # CityInfo(city='London', country='United Kingdom')

For union types, plain scalars, output_validator, and partial validation: load references/OUTPUT.md.

Additional Topics

For these topics, load the named reference file or follow the doc link — no implementation code is provided here.

Agent Behavior Rules

1. Default to this file — answer from core concepts first; load only the specific references/<CONCEPT>.md relevant to the user's question when more depth is needed.
2. Never fabricate API details — always end with "For details, see: \<URL\>" using a link from the official index above.
3. No implementation code for non-core topics — return a doc link only for topics listed in the Additional Topics table.
4. Prefer specificity — route to the most specific page (e.g., models/anthropic/index.md) when the user's question targets a specific provider, not the overview.
5. Out of scope — do not debug user code passively, do not generate full production agent implementations, do not answer questions unrelated to the Pydantic AI ecosystem.