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Found 28 Skills
Backend services development with Python emphasizing security, performance, and maintainability for JARVIS AI Assistant
Coordinates logging, error handling, CORS, health checks, and API docs
DBOS Python SDK for building reliable, fault-tolerant applications with durable workflows. Use this skill when writing Python code with DBOS, creating workflows and steps, using queues, using DBOSClient from external applications, or building applications that need to be resilient to failures.
Creates repository following Clean Architecture with Protocol in domain layer and Implementation in infrastructure layer. Use when adding new data access layer, creating database interaction, implementing persistence, or need to store/retrieve domain models. Enforces Protocol/ABC pattern with ServiceResult, ManagedResource lifecycle, and proper layer separation. Triggers on "create repository for X", "implement data access for Y", "add persistence layer", or "store/retrieve domain model".
Use when scaffolding production-ready FastAPI services with uv, SQLAlchemy, Alembic, Postgres, Docker, and CI gates.
Pydantic models and validation. Use when: (1) Defining schemas, (2) Validating input/output, (3) Generating JSON schema.
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.
Quick reference mapping global architecture concepts to Python/FastAPI/SQLAlchemy syntax. For concepts, see the global skills.
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.
Expert-level Flask web development, REST APIs, extensions, and production deployment