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 andregusman-raiz/a-gusman-claude --skill ag-referencia-pythongit clone --depth 1 https://github.com/andregusman-raiz/a-gusman-claudeWrote 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/andregusman-raiz/a-gusman-claude/ag-referencia-python)<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-referencia-python"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-referencia-python/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/andregusman-raiz/a-gusman-claude/ag-referencia-python"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-referencia-python.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 | $0.00020 | $0.00979 |
| Opus 5.5 | $0.00008 | $0.00392 |
| Sonnet 5.5 | $0.00004 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
ag-referencia-python 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 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.
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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Python Patterns
Referencia de patterns para projetos Python.
Quando Ativar
- Trabalhando em projeto Python
- Configurando ambiente virtual
- Escrevendo testes com pytest
Estrutura Recomendada
projeto/
├── README.md
├── requirements.txt
├── requirements-dev.txt
├── pyproject.toml
├── .env.example
├── src/
│ └── nome_projeto/
│ ├── __init__.py
│ ├── main.py
│ ├── config.py
│ ├── models/
│ ├── services/
│ ├── repositories/
│ └── utils/
├── tests/
│ ├── conftest.py
│ ├── test_models/
│ └── test_services/
└── scripts/
Ambiente Virtual
python -m venv .venv
source .venv/bin/activate # Linux/Mac
.venv\Scripts\activate # Windows
pip install -r requirements.txt
pip freeze > requirements.txt
Type Hints
from typing import Optional
from dataclasses import dataclass
def greet(name: str) -> str:
return f"Ola, {name}!"
def find_user(user_id: str) -> Optional["User"]:
...
def process_items(items: list[str]) -> dict[str, int]:
return {item: len(item) for item in items}
@dataclass
class User:
id: str
email: str
name: str
age: int | None = None
Pydantic (Validacao)
from pydantic import BaseModel, EmailStr, Field
from uuid import UUID, uuid4
class UserCreate(BaseModel):
email: EmailStr
name: str = Field(min_length=1, max_length=255)
class User(UserCreate):
id: UUID = Field(default_factory=uuid4)
class Config:
from_attributes = True
Pytest
# tests/conftest.py
import pytest
@pytest.fixture
def sample_user():
return User(id="123", email="[email protected]", name="Test")
# tests/test_services/test_user_service.py
class TestUserService:
def test_create_user_success(self, mock_db):
service = UserService(db=mock_db)
user = service.create(email="[email protected]", name="Test")
assert user.email == "[email protected]"
@pytest.mark.parametrize("email,valid", [
("[email protected]", True),
("invalid", False),
])
def test_validate_email(self, email: str, valid: bool):
assert UserService.validate_email(email) == valid
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 · 180 lines · 20 tokens per session scan A 111ded41c616
ag-referencia-python is a skill published in the GitHub repository andregusman-raiz/a-gusman-claude (18 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 979 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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