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 toffyui/ccteams --skill python-fastapi-playbookgit clone --depth 1 https://github.com/toffyui/ccteamsWrote 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/toffyui/ccteams/python-fastapi-playbook)<a href="https://agentmods.dev/skills/toffyui/ccteams/python-fastapi-playbook"><img src="https://agentmods.dev/badge/skills/toffyui/ccteams/python-fastapi-playbook/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/toffyui/ccteams/python-fastapi-playbook"><img src="https://agentmods.dev/badge/skills/toffyui/ccteams/python-fastapi-playbook.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.04157 |
| Opus 5.5 | $0.00022 | $0.01663 |
| Sonnet 5.5 | $0.00011 | $0.00831 |
| Haiku 4.5 | $0.00006 | $0.00416 |
Grade A, and why
python-fastapi-playbook scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
an `async def`: `requests.get`, `time.sleep`, `open().read()`, a sync DB How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python FastAPI Playbook
This is the literal procedure a frontier model follows when building or fixing
FastAPI services. Follow it step by step; the order is the point. FastAPI +
async is unforgiving in one specific way: code that works in a unit test
(one request, no concurrency) can stall the whole process under load because
a single blocking call in an async def freezes the event loop for every
other request. The type checker will not catch that. Those checks are yours.
Operating loop
- Read
pyproject.toml/requirements.txtFIRST — the Pydantic major version changes everything.grep -E "pydantic" pyproject.toml requirements.txtorpython -c "import pydantic; print(pydantic.VERSION)". v1 and v2 have different method names, validator decorators, and config styles (catalog below). Writing v2 idioms into a v1 project (or vice versa) produces import errors or silent no-ops. Note the package manager too:poetry.lock→poetry run,uv.lock→uv run, elsepython -m. - Find the local dialect and mirror it. Before writing a route, read two
existing routers:
grep -rn "APIRouter\|@router\.\|@app\." --include="*.py" .. Copy the project's router registration, response envelope, error-raising style (HTTPExceptionvs custom handler), and dependency wiring exactly. A "cleaner" pattern that differs from the neighbors is a defect here. - Find the schema and dependency patterns and mirror them. Read one
request model, one response model, and one
Dependsfunction. Match where validation lives (in the model, not the handler) and how sessions are acquired (yielddependency, not inline). - Boot the app early to catch import-time errors. Run the project's
entrypoint (
uvicorn app.main:appbriefly, orpython -c "import app.main", adjust to the real module path). FastAPI executes decorators, dependency signatures, and Pydantic model definitions at import time — a bad type annotation or a v1/v2 mismatch fails here, before any request. Do this again after your change. - For every path operation, decide
async defvsdefout loud (tree A). The choice is dictated by what the body calls, not by preference. - For every value crossing the HTTP boundary, put validation in a Pydantic
model (tree C) — not in
ifchecks inside the handler. - Run the verification recipe (below) and re-read your diff hunting for
blocking calls in
async def, missingawait, and handlers returning ORM objects without aresponse_model.
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 · 251 lines · 56 tokens per session scan A 3b8244c2f95e
python-fastapi-playbook is a skill published in the GitHub repository toffyui/ccteams (48 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 4,157 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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