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Found 106 Skills
Generate AI-friendly Python CLIs using Click, Pydantic, and uv. Use when user wants to create a new CLI tool that follows best practices for agentic coding environments.
Design Pydantic models and LLM prompt templates for structured extraction pipelines. Use when creating, editing, or reviewing Pydantic models that serve as LLM output schemas, or when writing prompt templates that pair with those models. Trigger: "pydantic model", "structured output", "extraction schema", "LLM output model", "schema design".
Generate and validate environment-based configuration for Python apps using Pydantic or Dynaconf. Use to ensure secure and valid runtime settings.
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.
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.
Build agentic UIs using AG-UI protocol with Pydantic AI (Python backend) and CopilotKit (React/Next.js frontend). Use when creating AI-powered applications that need bidirectional agent-UI communication, shared state between frontend and backend, human-in-the-loop workflows, tool-based generative UI, or predictive state updates. Triggers on requests involving CopilotKit hooks (useCoAgent, useCopilotAction, useCoAgentStateRender), pydantic_ai with ag_ui adapters, or building chat interfaces with backend AI agents.
Debug FastAPI applications systematically with this comprehensive troubleshooting skill. Covers async/await issues, Pydantic validation errors (422 responses), dependency injection failures, CORS configuration problems, database session management, and circular import resolution. Provides structured four-phase debugging methodology with FastAPI-specific tools including uvicorn logging, OpenAPI docs, and middleware debugging patterns.
Query Logfire telemetry data — traces, logs, spans, and metrics. Use this skill when the user asks to "query logfire", "search traces", "find logs", "query data", "search spans", "look up errors in logfire", "get metrics from logfire", "analyze telemetry", or wants to add Logfire querying capabilities to their code. Also use when the user wants to explore OpenTelemetry data, investigate production issues by querying, or build dashboards/reports from Logfire data.
Review Python code for quality, security, and best practices