python-standards

Guidance for writing, reviewing, and testing Python code, including naming, formatting, imports, and common project tools.

In plain words
What is it for?
Use it when building or reviewing Python projects, especially projects using tools such as uv, FastAPI, or Pydantic.
Why use it?
It keeps Python code consistent and easier for a team to read, maintain, and check.

Skill for Claude CodeCodex

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 skills/shwilliamson/automatasaurus/python-standards
Any agent
npx skills add shwilliamson/automatasaurus --skill python-standards
Clone the repo
git clone --depth 1 https://github.com/shwilliamson/automatasaurus

Made for: Claude Code, Codex.

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,559 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 $0.00026 $0.01559
Opus 5 $0.00013 $0.00779
Sonnet 5 $0.00005 $0.00312
Haiku 4.5 $0.00003 $0.00156

Measured 2d ago against content hash aaabbb7397dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-standards 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.

template/skills/python-standards/SKILL.md · 285 lines

How it starts

The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Coding Standards

New Project Preferences

When starting new Python projects, prefer:

  • uv for package/environment management (fast, modern alternative to pip/venv)
  • FastAPI for web APIs
  • Pydantic for data validation and serialization

Style Guide

Follow PEP 8 with these project-specific additions:

Formatting

  • Line length: 88 characters (Black default)
  • Use Black for formatting, isort for imports
  • Use double quotes for strings (Black default)

Naming Conventions

# Modules and packages: lowercase_with_underscores
user_service.py

# Classes: PascalCase
class UserService:
    pass

# Functions and variables: snake_case
def get_user_by_id(user_id: int) -> User:
    active_users = []

# Constants: SCREAMING_SNAKE_CASE
MAX_RETRY_ATTEMPTS = 3
DEFAULT_TIMEOUT_SECONDS = 30

# Private: single leading underscore
def _internal_helper():
    pass

# "Private" (name mangling): double leading underscore (rare)
class Base:
    def __private_method(self):
        pass

Imports

# Order: stdlib, third-party, local (isort handles this)
import os
import sys
from pathlib import Path

import requests
from pydantic import BaseModel

from app.models import User
from app.services import UserService

Type Hints

Always use type hints for function signatures:

from typing import Optional, List, Dict, Any, Union
from collections.abc import Sequence, Mapping

def process_users(
    users: List[User],
    filter_active: bool = True,
    metadata: Optional[Dict[str, Any]] = None,
) -> List[ProcessedUser]:
    """Process a list of users with optional filtering."""
    ...

# Use | for unions (Python 3.10+)
def get_value(key: str) -> str | None:
    ...

Docstrings

Use Google-style docstrings:

def fetch_user(user_id: int, include_deleted: bool = False) -> User:
    """Fetch a user by their ID.

    Args:
        user_id: The unique identifier of the user.
        include_deleted: Whether to include soft-deleted users.

    Returns:
        The User object if found.

    Raises:
        UserNotFoundError: If no user exists with the given ID.
        DatabaseConnectionError: If the database is unavailable.
    """
    ...

Read the full file on GitHub · 285 lines

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 · 285 lines · 26 tokens per session scan A aaabbb7397dd

Subscribe to this mod's changes

python-standards is a skill published in the GitHub repository shwilliamson/automatasaurus (5 stars, last pushed 6mo ago), licensed MIT. It adds 26 tokens to every session and 1,559 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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