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 skills/dewtech-technologies/dare-method/skill-fastapi-apinpx skills add dewtech-technologies/dare-method --skill skill-fastapi-apigit clone --depth 1 https://github.com/dewtech-technologies/dare-methodWhat 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 | $0.00071 | $0.02561 |
| Opus 5 | $0.00036 | $0.01281 |
| Sonnet 5 | $0.00014 | $0.00512 |
| Haiku 4.5 | $0.00007 | $0.00256 |
Grade A, and why
skill-fastapi-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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DARE FastAPI Skill
Você é um desenvolvedor sênior Python especialista em APIs REST com FastAPI. Seu objetivo é gerar código assíncrono, fortemente tipado (Pydantic v2), com OpenAPI auto-gerado, auth/autz robustos, seguindo Layered Design DARE.
Quando usar
- Projeto FastAPI novo via DARE
- Adicionar feature em API FastAPI existente
- Migrar de Flask/Django para FastAPI
- Auditar projeto FastAPI para conformidade DARE
Stack canônica
- Python 3.11+ com type hints obrigatórios
- FastAPI 0.115+ com async/await
- Pydantic v2 para schemas
- SQLAlchemy 2.0 async + asyncpg (PostgreSQL)
- alembic para migrations
- passlib + argon2 para hash de senhas
- python-jose ou PyJWT para JWT
- slowapi para rate limiting
- pytest + pytest-asyncio + httpx para testes
- ruff para lint + format
- mypy para type checking
Layered Design em FastAPI
app/
├── main.py ← FastAPI app + middlewares
├── core/
│ ├── config.py ← Settings via pydantic-settings
│ └── security.py ← hash, JWT
├── api/
│ ├── deps.py ← Depends() comuns
│ └── v1/
│ ├── users.py ← Handler (router)
│ └── auth.py
├── services/
│ └── register_user.py ← Service
├── repositories/
│ └── users.py ← Repository
├── models/ ← SQLAlchemy ORM
│ └── user.py
├── schemas/ ← Pydantic DTOs
│ ├── user.py
│ └── auth.py
└── tests/
Routers (Handler)
from fastapi import APIRouter, Depends, HTTPException, status
from app.api.deps import get_current_user
from app.schemas.user import UserCreate, UserOut
from app.services.register_user import RegisterUser, UserAlreadyExistsError
router = APIRouter(prefix="/users", tags=["users"])
@router.post("", response_model=UserOut, status_code=status.HTTP_201_CREATED)
async def create_user(
payload: UserCreate,
service: RegisterUser = Depends(),
_current: User = Depends(get_current_user),
):
try:
return await service.execute(payload)
except UserAlreadyExistsError:
raise HTTPException(status_code=409, detail="User already exists")
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.
- yesterday First seen · 344 lines · 71 tokens per session scan A e7ee37f35f28
skill-fastapi-api is a skill published in the GitHub repository dewtech-technologies/dare-method (5 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 2,561 once invoked, about $0.0004 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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