Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/hamzapixl/pixl-ai/fastapi-apinpx skills add hamzaPixl/pixl-ai --skill fastapi-apigit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hamzapixl/pixl-ai/fastapi-api)<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/fastapi-api"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/fastapi-api.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.00420 |
| Opus 5 | $0.00039 | $0.00210 |
| Sonnet 5 | $0.00016 | $0.00084 |
| Haiku 4.5 | $0.00008 | $0.00042 |
Grade A, and why
fastapi-api scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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
- Define the API's entities and relationships
- Design the URL structure and HTTP methods
- Choose authentication method (JWT, API keys, OAuth)
- Plan database schema
Phase 2: Scaffold
- Run
/fastapi-serviceto scaffold the base service - Set up database (SQLAlchemy models, migrations)
- Add authentication middleware
Phase 3: Implement
- For each entity, run
/pydantic-api-endpointto add CRUD endpoints - Add business logic and validation rules
- Add inter-entity relationships and nested routes
- Add pagination, filtering, and sorting
Phase 4: Quality & Deploy
- Write tests for each endpoint (happy path + edge cases)
- Run
/self-review-fix-loopfor quality assurance - Add OpenAPI documentation (auto-generated by FastAPI)
- Run
/docker-cloudrunfor containerization and deployment - Verify: all tests pass, API documentation accessible, health check responds
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 48 lines · 79 tokens per session scan A b92922d9384e
fastapi-api is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 79 tokens to every session and 420 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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