scaffold-api

A command that creates a new FastAPI web-service project using separate folders for API routes, business logic, database access, data models, and tests.

In plain words
What is it for?
Use it to scaffold a FastAPI project for entities such as users, products, or orders, including SQLAlchemy database files, Pydantic models, routes, and tests.
Why use it?
Starting an API from scratch involves repeating setup work and deciding how to organize its code. This command creates the stated project structure and asks which main data types the API needs.

Command

Install

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.

agentmods
npx agentmods add commands/mktoronto/python-clean-architecture/scaffold-api
Clone the repo
git clone --depth 1 https://github.com/MKToronto/python-clean-architecture
Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 565 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2d ago against content hash b5844b74dc31, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

commands/scaffold-api.md · 50 lines

What it actually says

Generate a new FastAPI project named $ARGUMENTS with the three-layer clean architecture structure.

Process

  1. Ask for entities — Use AskUserQuestion: "What are the main entities for this API? (e.g., users, products, orders)" to determine what to scaffold.

  2. 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
    
  3. 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 DataInterfaceStub with no database dependency
  4. Wire it togethermain.py includes 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.

Changes

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.

  1. 2d ago First seen · 50 lines · 13 tokens per session scan A b5844b74dc31

Subscribe to this mod's changes

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.