# Hamzapixl Pixl AI Fastapi API > Overview - Skill: `tomevault-io/hamzapixl-pixl-ai-fastapi-api` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/hamzapixl-pixl-ai-fastapi-api` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/hamzapixl-pixl-ai-fastapi-api/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Integrations & APIs - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/hamzapixl-pixl-ai-fastapi-api --- ## Overview Builds a complete FastAPI backend: scaffolds the service, adds CRUD endpoints for each entity, sets up authentication, and deploys. ## Suggested Team - **architect** — API design, data model, authentication strategy - **backend-engineer** — Service implementation, endpoint creation - **qa-engineer** — Test writing, API testing ## Process ### Phase 1: Design 1. Define the API's entities and relationships 2. Design the URL structure and HTTP methods 3. Choose authentication method (JWT, API keys, OAuth) 4. Plan database schema ### Phase 2: Scaffold 5. Run `/fastapi-service` to scaffold the base service 6. Set up database (SQLAlchemy models, migrations) 7. Add authentication middleware ### Phase 3: Implement 8. For each entity, run `/pydantic-api-endpoint` to add CRUD endpoints 9. Add business logic and validation rules 10. Add inter-entity relationships and nested routes 11. Add pagination, filtering, and sorting ### Phase 4: Quality & Deploy 12. Write tests for each endpoint (happy path + edge cases) 13. Run `/self-review-fix-loop` for quality assurance 14. Add OpenAPI documentation (auto-generated by FastAPI) 15. Run `/docker-cloudrun` for containerization and deployment 16. Verify: all tests pass, API documentation accessible, health check responds --- > Source: [hamzaPixl/pixl-ai](https://github.com/hamzaPixl/pixl-ai) — distributed by [TomeVault](https://tomevault.io).