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/add-endpointgit 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 | $0.00014 | $0.00505 |
| Opus 5 | $0.00007 | $0.00253 |
| Sonnet 5 | $0.00003 | $0.00101 |
| Haiku 4.5 | $0.00001 | $0.00051 |
Grade A, and why
add-endpoint 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
Scaffold a new endpoint for $ARGUMENTS across all three layers of the clean architecture.
Process
-
Understand the project — Read the existing project structure to understand naming conventions, existing patterns, and where files live. Identify the routers/, operations/, db/, and models/ directories.
-
Ask for details — Use AskUserQuestion to clarify:
- "What operations does this endpoint need?" with options: CRUD (all), Read-only, Custom (describe)
-
Generate across all layers — Create or update files in each layer:
Models layer (
models/{entity}.py):{Entity}Create— Pydantic model for creation input{Entity}— Pydantic model for read output (includes id){Entity}Update— Pydantic model for partial updates (all fields optional)DataInterfaceProtocol if not already defined, or extend existing one
Operations layer (
operations/{entity}.py):- Business logic functions that accept
data_interface: DataInterface create_{entity}(),get_{entity}(),list_{entities}(),update_{entity}(),delete_{entity}()- No database imports — only depends on the Protocol
Database layer (
db/models.py):- SQLAlchemy ORM model for the entity
- Extend
DBInterfaceif using generic implementation, or add methods to existing DB class
Router layer (
routers/{entity}.py):APIRouterwith CRUD endpoints- Acts as composition root — instantiates/injects concrete DB into operations
- Proper HTTP methods and status codes (201 for create, 204 for delete)
Tests (
tests/test_{entity}.py):- Tests using
DataInterfaceStub— no database needed - Cover create, read, update, delete, and not-found cases
-
Update main.py — Add
include_router()for the new router.
Follow existing project conventions for naming, imports, and style. Consult ${CLAUDE_PLUGIN_ROOT}/skills/clean-architecture/references/layered-architecture.md for the layer patterns.
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 · 45 lines · 14 tokens per session scan A ee88a5f908a3
add-endpoint is a command published in the GitHub repository MKToronto/python-clean-architecture (8 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 505 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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