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Found 105 Skills
Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library
Server-specific best practices for FastAPI, Celery, and Pydantic. Extends python-skills with framework-specific patterns.
Integrate with Affinda's document AI API to extract structured data from documents (invoices, resumes, receipts, contracts, and custom types). Covers authentication, client libraries (Python, TypeScript), structured outputs with Pydantic models and TypeScript interfaces, webhooks, upload patterns, and the full documentation map. Use when building integrations that parse, classify, or extract data from documents using Affinda.
Expert guidance for SQLAlchemy 2.0 + Pydantic + PostgreSQL. Use when setting up database layers, defining models, creating migrations, or any database-related work. Automatically activated for DB tasks.
Validate API requests with schemas, sanitization, and helpful error messages. Covers Zod, Joi, and Pydantic patterns.
API contract design conventions for FastAPI projects with Pydantic v2. Use during the design phase when planning new API endpoints, defining request/response contracts, designing pagination or filtering, standardizing error responses, or planning API versioning. Covers RESTful naming, HTTP method semantics, Pydantic v2 schema naming conventions (XxxCreate/XxxUpdate/XxxResponse), cursor-based pagination, standard error format, and OpenAPI documentation. Does NOT cover implementation details (use python-backend-expert) or system-level architecture (use system-architecture).
Dual skill for deploying scientific models. FastAPI provides a high-performance, asynchronous web framework for building APIs with automatic documentation. Streamlit enables rapid creation of interactive data applications and dashboards directly from Python scripts. Load when working with web APIs, model serving, REST endpoints, interactive dashboards, data visualization UIs, scientific app deployment, async web frameworks, Pydantic validation, uvicorn, or building production-ready scientific tools.
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.
FastAPI production-grade best practices and guidelines for building scalable, high-performance web APIs. Covers project structure, async concurrency, Pydantic validation, dependency injection, and database patterns.
Audits and enhances API documentation for FastAPI and REST endpoints. Identifies missing descriptions, incomplete response codes, missing examples, and generates enhanced docstrings, Pydantic model examples, and OpenAPI spec improvements. Triggers on: "generate API docs", "document this API", "OpenAPI for", "add examples to", "improve docstrings", "API documentation audit", "FastAPI docs", "document endpoints", "API reference", "swagger docs", "REST API docs", "endpoint documentation", "response documentation". Use this skill when API endpoints need documentation or documentation audit.
Expert FastAPI developer specializing in production-ready async REST APIs with Pydantic v2, SQLAlchemy 2.0, OAuth2/JWT authentication, and comprehensive security. Deep expertise in dependency injection, background tasks, async database operations, input validation, and OWASP security best practices. Use when building high-performance Python web APIs, implementing authentication systems, or securing API endpoints.
FastAPI advanced patterns including lifespan, dependencies, middleware, and Pydantic settings. Use when configuring FastAPI lifespan events, creating dependency injection, building Starlette middleware, or managing async Python services with uvicorn.