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Found 107 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
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.
LangGraph state management patterns. Use when designing workflow state schemas, using TypedDict vs Pydantic, implementing accumulating state with Annotated operators, or managing shared state across nodes.
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).
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization, or API architecture.
Plan and build production-ready FastAPI endpoints with async SQLAlchemy, Pydantic v2 models, dependency injection for auth, and pytest tests. Uses interview-driven planning to clarify data models, authentication method, pagination strategy, and caching before writing any code.
Create Galaxy REST API endpoints with FastAPI routers, Pydantic schemas, and manager pattern. Use for: new API routes, FastAPI endpoints, REST resources, Pydantic request/response models, lib/galaxy/webapps/galaxy/api routers, lib/galaxy/schema definitions, API controller creation.
Guidelines for building RoboCorp RPA automation with Python, emphasizing functional programming, Pydantic validation, and async operations.
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.
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.
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.