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/b33eep/claude-code-setup/standards-pythonnpx skills add b33eep/claude-code-setup --skill standards-pythongit clone --depth 1 https://github.com/b33eep/claude-code-setupWhat 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 | $0.00030 | $0.01511 |
| Opus 5 | $0.00015 | $0.00756 |
| Sonnet 5 | $0.00006 | $0.00302 |
| Haiku 4.5 | $0.00003 | $0.00151 |
Grade A, and why
standards-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 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.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Coding Standards
Core Principles
- Simplicity: Simple, understandable code
- Readability: Readability over cleverness
- Maintainability: Code that's easy to maintain
- Testability: Code that's easy to test
- DRY: Don't Repeat Yourself - but don't overdo it
General Rules
- Early Returns: Use early returns to avoid nesting
- Descriptive Names: Meaningful names for variables and functions
- Minimal Changes: Only change relevant code parts
- No Over-Engineering: No unnecessary complexity
- Minimal Comments: Code should be self-explanatory. No redundant comments!
Naming Conventions
| Element | Convention | Example |
|---|---|---|
| Variables/Functions | snake_case | get_user_by_id, is_active |
| Classes | PascalCase | UserService, ApiClient |
| Constants | UPPER_SNAKE_CASE | MAX_RETRY_COUNT |
| Private | Prefix with _ |
_internal_method |
| Files/Modules | snake_case | user_service.py |
Project Structure
myproject/
├── src/
│ ├── __init__.py
│ ├── main.py # Entry point
│ ├── config.py # Settings, env vars
│ ├── models.py # Domain models (dataclasses/Pydantic)
│ ├── schemas.py # Request/response DTOs
│ ├── services/
│ │ ├── __init__.py
│ │ └── user_service.py # Business logic
│ └── repositories/
│ ├── __init__.py
│ └── user_repo.py # Data access
├── tests/
│ ├── __init__.py
│ ├── test_services.py
│ └── test_repositories.py
├── pyproject.toml
└── README.md
Code Style (PEP 8 + PEP 484)
from dataclasses import dataclass
@dataclass
class User:
id: str
name: str
email: str
age: int | None = None # Python 3.10+ union syntax
def get_user_by_id(user_id: str) -> User | None:
if not user_id:
raise ValueError("user_id cannot be empty")
# implementation...
Best Practices
# Type hints everywhere
def process_items(items: list[str]) -> dict[str, int]:
return {item: len(item) for item in items}
# Pydantic v2 for validation
from pydantic import BaseModel, Field, field_validator, EmailStr
class UserCreate(BaseModel):
name: str = Field(..., min_length=2, max_length=50)
email: EmailStr
age: int | None = Field(None, ge=0, le=150)
@field_validator('name')
@classmethod
def name_must_be_alphanumeric(cls, v: str) -> str:
if not v.replace(' ', '').isalnum():
raise ValueError('Name must be alphanumeric')
return v.strip()
# Context managers
with open('file.txt', 'r') as f:
content = f.read()
# Prefer pathlib over os.path
from pathlib import Path
config_path = Path(__file__).parent / 'config.yaml'
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 191 lines · 30 tokens per session scan A f0daa540aa13
standards-python is a skill published in the GitHub repository b33eep/claude-code-setup (56 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 1,511 once invoked, about $0.0002 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 2026-08-30.
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