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 skills add Cypsy1714/cchad --skill fastapi-skillgit clone --depth 1 https://github.com/Cypsy1714/cchadWrote 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/cypsy1714/cchad/fastapi-skill)<a href="https://agentmods.dev/skills/cypsy1714/cchad/fastapi-skill"><img src="https://agentmods.dev/badge/skills/cypsy1714/cchad/fastapi-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cypsy1714/cchad/fastapi-skill"><img src="https://agentmods.dev/badge/skills/cypsy1714/cchad/fastapi-skill.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00026 | $0.00292 |
| Opus 5.5 | $0.00010 | $0.00117 |
| Sonnet 5.5 | $0.00005 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
fastapi-conventions 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 1mo 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
FastAPI conventions
Guidance for building FastAPI services that stay clean under growth.
Structure
- Group routes with
APIRouterper resource; keep one router per module. - Put request/response shapes in Pydantic models. Never accept or return raw
dicts at the boundary — let the schema validate. - Separate the web layer (routers) from business logic (services) so handlers stay thin.
Dependencies
- Use
Depends()for shared concerns: database sessions, the current user, settings. Don't reach for globals. - Build a single settings object with
pydantic-settingsand inject it, rather than readingos.environthroughout the code.
Async
- If a handler does I/O, make it
asyncand use async clients. Never call a blocking library inside an async handler — offload it withrun_in_threadpool. - Open and close resources (DB sessions, HTTP clients) with dependencies or lifespan handlers, not per-request globals.
Errors & validation
- Raise
HTTPExceptionwith a precise status code; let Pydantic return 422 for bad input automatically. - Return explicit response models so the OpenAPI schema stays accurate.
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.
- 1mo ago First seen · 33 lines · 26 tokens per session scan A aaa7ba0f13cc
fastapi-conventions is a skill published in the GitHub repository Cypsy1714/cchad (1 stars, last pushed 3mo ago), licensed MIT. It adds 26 tokens to every session and 292 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
cortex-integrate
Design and implement an AI feature integration — model selection, architecture pattern, system prompt, data flow, error handling, cost estimate. Use when asked to "add AI to this", "LLM integration", "add Claude/GPT", or "AI-powered feature".
spine-api
Design and spec an API — endpoints, request/response shapes, error codes, auth pattern, pagination. Applies Stripe's consistency principles. Use when asked to "design an API", "build API endpoints", "create REST API", or "API for this feature".
spine-design
Produce a system design doc — components, data flow, decisions made, tradeoffs, failure modes. Not a list of options. An actual design with calls made. Use when asked for "system design for", "architect this", "how should we build", or "design the backend".
warden-harden
Produce a hardening spec and implement it — auth patterns, security headers, rate limiting, input validation, secrets management, dependency hygiene. Use when asked to "harden this", "add security to this service", "what security do I need", or "secure this before launch".
spine-perf
Find and fix performance bottlenecks — N+1 queries, missing indexes, sync bottlenecks, caching gaps. Use when asked "why is this slow", "performance issue", "optimize this endpoint", or "N+1 queries".
spine-review
API and backend code review — REST conventions, auth, validation, error handling, pagination, rate limiting, test coverage. Use when asked to "review this API", "code review", "review backend", or "pre-launch backend check".