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/luohaothu/everything-codex/python-testingnpx skills add Luohaothu/everything-codex --skill python-testinggit clone --depth 1 https://github.com/Luohaothu/everything-codexWhat 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 | $0.00026 | $0.04607 |
| Opus 5 | $0.00013 | $0.02303 |
| Sonnet 5 | $0.00005 | $0.00921 |
| Haiku 4.5 | $0.00003 | $0.00461 |
Grade A, and why
python-testing scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get("https://api.example.com") How it starts
The opening of the file, as written. The whole thing — 816 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python 测试模式
使用 pytest、TDD 方法论和最佳实践的 Python 应用程序全面测试策略。
何时激活
- 编写新的 Python 代码(遵循 TDD:红、绿、重构)
- 为 Python 项目设计测试套件
- 审查 Python 测试覆盖率
- 设置测试基础设施
核心测试理念
测试驱动开发 (TDD)
始终遵循 TDD 循环:
- 红:为期望的行为编写一个失败的测试
- 绿:编写最少的代码使测试通过
- 重构:在保持测试通过的同时改进代码
# Step 1: Write failing test (RED)
def test_add_numbers():
result = add(2, 3)
assert result == 5
# Step 2: Write minimal implementation (GREEN)
def add(a, b):
return a + b
# Step 3: Refactor if needed (REFACTOR)
覆盖率要求
- 目标:80%+ 代码覆盖率
- 关键路径:需要 100% 覆盖率
- 使用
pytest --cov来测量覆盖率
pytest --cov=mypackage --cov-report=term-missing --cov-report=html
pytest 基础
基本测试结构
import pytest
def test_addition():
"""Test basic addition."""
assert 2 + 2 == 4
def test_string_uppercase():
"""Test string uppercasing."""
text = "hello"
assert text.upper() == "HELLO"
def test_list_append():
"""Test list append."""
items = [1, 2, 3]
items.append(4)
assert 4 in items
assert len(items) == 4
断言
# Equality
assert result == expected
# Inequality
assert result != unexpected
# Truthiness
assert result # Truthy
assert not result # Falsy
assert result is True # Exactly True
assert result is False # Exactly False
assert result is None # Exactly None
# Membership
assert item in collection
assert item not in collection
# Comparisons
assert result > 0
assert 0 <= result <= 100
# Type checking
assert isinstance(result, str)
# Exception testing (preferred approach)
with pytest.raises(ValueError):
raise ValueError("error message")
# Check exception message
with pytest.raises(ValueError, match="invalid input"):
raise ValueError("invalid input provided")
# Check exception attributes
with pytest.raises(ValueError) as exc_info:
raise ValueError("error message")
assert str(exc_info.value) == "error message"
夹具
基本夹具使用
import pytest
@pytest.fixture
def sample_data():
"""Fixture providing sample data."""
return {"name": "Alice", "age": 30}
def test_sample_data(sample_data):
"""Test using the fixture."""
assert sample_data["name"] == "Alice"
assert sample_data["age"] == 30
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 · 816 lines · 26 tokens per session scan A a32ca141a566
python-testing is a skill published in the GitHub repository Luohaothu/everything-codex (24 stars, last pushed 21d ago), licensed MIT. It adds 26 tokens to every session and 4,607 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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