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Found 35 Skills
Build high-performance APIs with Django-Bolt, including BoltAPI routes, typed request validation, msgspec serialization, auth guards, middleware, OpenAPI docs, pagination, streaming, SSE, WebSockets, and testing. Use when the user asks to create a new bolt endpoint, set up a Django-Bolt project, add JWT or API key auth, configure runbolt, wire guards or middleware, add pagination or streaming, generate OpenAPI docs, write TestClient tests, or migrate from FastAPI, Django REST Framework, or Django Ninja to django-bolt. Do NOT use for general Django views, Django admin customization, or standard Django REST Framework work.
Backend services development with Python emphasizing security, performance, and maintainability for JARVIS AI Assistant
FastAPI dev/prod runbook (Uvicorn reload, Gunicorn)
Pydantic models and validation. Use when: (1) Defining schemas, (2) Validating input/output, (3) Generating JSON schema.
Use when securing FastAPI API endpoints with JWT Bearer token validation, scope/permission checks, or stateless auth - integrates auth0-fastapi-api for REST APIs receiving access tokens from SPAs, mobile apps, or other clients. Also handles DPoP proof-of-possession token binding. Triggers on: Auth0FastAPI, FastAPI API auth, JWT validation, require_auth, DPoP.
Coordinates logging, error handling, CORS, health checks, and API docs
Example of a properly self-contained skill following all best practices
Principal backend engineering intelligence for Python services and data systems. Actions: plan, design, build, implement, review, fix, optimize, refactor, debug, secure, scale backend code and architectures. Focus: correctness, reliability, performance, security, observability, scalability, operability, cost.
Implements search and filter interfaces for both frontend (React/TypeScript) and backend (Python) with debouncing, query management, and database integration. Use when adding search functionality, building filter UIs, implementing faceted search, or optimizing search performance.
Comprehensive guide for production-ready Python backend development and software architecture at scale. Use when designing APIs, building backend services, creating microservices, structuring Python projects, implementing database patterns, writing async code, or any Python backend/server-side development task. Covers Clean Architecture, Domain-Driven Design, Event-Driven Architecture, FastAPI/Django patterns, database design, caching strategies, observability, security, testing strategies, and deployment patterns for high-scale production systems.
Build FastAPI applications using Clean Architecture principles with proper layer separation (Domain, Infrastructure, API), dependency injection, repository pattern, and comprehensive testing. Use this skill when designing or implementing Python backend services that require maintainability, testability, and scalability.
Guides FastAPI backend design using Domain-Driven Design (DDD) and Onion Architecture in Python. Use when structuring a FastAPI app (routes/handlers, Pydantic schemas, Depends-based DI), modeling domain Entities/Value Objects, defining repository interfaces, implementing SQLAlchemy infrastructure adapters, or writing use cases, based on the dddpy reference.