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 commands/mktoronto/python-clean-architecture/scaffold-apigit clone --depth 1 https://github.com/MKToronto/python-clean-architectureWhat 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 | $0.00013 | $0.00565 |
| Opus 5 | $0.00006 | $0.00282 |
| Sonnet 5 | $0.00003 | $0.00113 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
scaffold-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 2d 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
Generate a new FastAPI project named $ARGUMENTS with the three-layer clean architecture structure.
Process
-
Ask for entities — Use AskUserQuestion: "What are the main entities for this API? (e.g., users, products, orders)" to determine what to scaffold.
-
Create project structure — Generate the full directory tree:
{project_name}/ ├── main.py # FastAPI app, include_router, startup ├── routers/ │ ├── __init__.py │ └── {entity}.py # APIRouter, endpoints, composition root ├── operations/ │ ├── __init__.py │ ├── interface.py # DataInterface Protocol + DataInterfaceStub │ └── {entity}.py # Business logic, accepts DataInterface ├── db/ │ ├── __init__.py │ ├── database.py # Engine, SessionLocal, Base │ ├── db_interface.py # Generic DBInterface implementing DataInterface │ └── models.py # SQLAlchemy ORM models ├── models/ │ ├── __init__.py │ └── {entity}.py # Pydantic Create/Read models ├── tests/ │ ├── __init__.py │ └── test_{entity}.py # Tests using DataInterfaceStub ├── requirements.txt └── .gitignore -
Generate files — For each entity, create:
- Pydantic models — separate Create and Read models
- Operations — business logic functions accepting
data_interface: DataInterface - Router — CRUD endpoints acting as composition root, injecting concrete DB
- DB model — SQLAlchemy ORM model
- Tests — using
DataInterfaceStubwith no database dependency
-
Wire it together —
main.pyincludes all routers and sets up the database.
Consult ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/layered-architecture.md and ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/testable-api.md for the full architecture patterns. Use ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/examples/fastapi-hotel-api/ as a working reference.
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.
- 2d ago First seen · 50 lines · 13 tokens per session scan A b5844b74dc31
scaffold-api is a command published in the GitHub repository MKToronto/python-clean-architecture (8 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 565 once invoked, about $0.0001 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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deploy
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save
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