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/fmarzochi/egc/python-patternsnpx skills add Fmarzochi/EGC --skill python-patternsgit clone --depth 1 https://github.com/Fmarzochi/EGCWhat 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 | $0.00045 | $0.02292 |
| Opus 5 | $0.00023 | $0.01146 |
| Sonnet 5 | $0.00009 | $0.00458 |
| Haiku 4.5 | $0.00005 | $0.00229 |
Grade A, and why
python-patterns 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.
This is a copy
100% identical to python-patterns — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Patterns
This skill provides comprehensive Python patterns extending common design principles with Python-specific idioms.
Protocol (Duck Typing)
Use Protocol for structural subtyping (duck typing with type hints):
from typing import Protocol
class Repository(Protocol):
def find_by_id(self, id: str) -> dict | None: ...
def save(self, entity: dict) -> dict: ...
# Any class with these methods satisfies the protocol
class UserRepository:
def find_by_id(self, id: str) -> dict | None:
# implementation
pass
def save(self, entity: dict) -> dict:
# implementation
pass
def process_entity(repo: Repository, id: str) -> None:
entity = repo.find_by_id(id)
# ... process
Benefits:
- Type safety without inheritance
- Flexible, loosely coupled code
- Easy testing and mocking
Dataclasses as DTOs
Use dataclass for data transfer objects and value objects:
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class CreateUserRequest:
name: str
email: str
age: Optional[int] = None
tags: list[str] = field(default_factory=list)
@dataclass(frozen=True)
class User:
"""Immutable user entity"""
id: str
name: str
email: str
Features:
- Auto-generated
__init__,__repr__,__eq__ frozen=Truefor immutabilityfield()for complex defaults- Type hints for validation
Context Managers
Use context managers (with statement) for resource management:
from contextlib import contextmanager
from typing import Generator
@contextmanager
def database_transaction(db) -> Generator[None, None, None]:
"""Context manager for database transactions"""
try:
yield
db.commit()
except Exception:
db.rollback()
raise
# Usage
with database_transaction(db):
db.execute("INSERT INTO users ...")
Class-based context manager:
class FileProcessor:
def __init__(self, filename: str):
self.filename = filename
self.file = None
def __enter__(self):
self.file = open(self.filename, 'r')
return self.file
def __exit__(self, exc_type, exc_val, exc_tb):
if self.file:
self.file.close()
return False # Don't suppress exceptions
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 · 429 lines · 45 tokens per session scan A 90bb7d10b9e9
python-patterns is a skill published in the GitHub repository Fmarzochi/EGC (46 stars, last pushed 5d ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,292 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to python-patterns, differing in 2 lines, and is treated as a copy.
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