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Found 96 Skills
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
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.
Generate and validate environment-based configuration for Python apps using Pydantic or Dynaconf. Use to ensure secure and valid runtime settings.
Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.
FastAPI web framework patterns. Triggers on: fastapi, api endpoint, dependency injection, pydantic model, openapi, swagger, starlette, async api, rest api, uvicorn.
FastAPI done right. Async patterns, dependency injection, Pydantic v2 models, middleware, and project structure.
Build typed LLM applications with PydanticAI: schema-constrained outputs, tool integration, validation, retries, and deterministic downstream handoffs. Use when users need reliable structured outputs instead of free-form text generation.
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.
This skill should be used when the user asks to "validate data with pydantic", "create a pydantic model", "use pydantic best practices", "write pydantic validators", or needs guidance on pydantic v2 patterns, serialization, configuration, or performance optimization.
FastAPI Python async framework with Pydantic and automatic OpenAPI. Use for Python APIs.
Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
Migrates Airflow projects from airflow-ai-sdk to apache-airflow-providers-common-ai 0.1.0+. Use this skill when the user wants to replace airflow-ai-sdk with the official Airflow AI provider, migrate LLM decorators (@task.llm, @task.agent, @task.llm_branch, @task.embed), switch from model strings/objects to connection-based LLM configuration, or update imports from airflow_ai_sdk to the new provider. Also trigger when the user mentions common-ai provider, AIP-99, pydanticai connection, or migrating away from airflow-ai-sdk.