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 CHENyiru3/AI-Skills-Collections --skill testing-strategygit clone --depth 1 https://github.com/CHENyiru3/AI-Skills-CollectionsWrote 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/chenyiru3/ai-skills-collections/testing-strategy)<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/testing-strategy"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/testing-strategy/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/chenyiru3/ai-skills-collections/testing-strategy"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/testing-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00068 | $0.00893 |
| Opus 5.5 | $0.00027 | $0.00357 |
| Sonnet 5.5 | $0.00014 | $0.00179 |
| Haiku 4.5 | $0.00007 | $0.00089 |
Grade A, and why
testing-python-libraries 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 6d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Library Testing
Quick Start
pytest # Run tests
pytest --cov=my_library # With coverage
pytest -x # Stop on first failure
pytest -k "test_encode" # Run matching tests
Pytest Configuration
# pyproject.toml
[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-ra -q --cov=my_library --cov-fail-under=85"
[tool.coverage.run]
branch = true
source = ["src/my_library"]
Test Structure
tests/
├── conftest.py # Shared fixtures
├── test_encoding.py
└── test_decoding.py
Essential Patterns
Basic test:
def test_encode_valid_input():
result = encode(37.7749, -122.4194)
assert isinstance(result, str)
assert len(result) == 12
Parametrization:
@pytest.mark.parametrize("lat,lon,expected", [
(37.7749, -122.4194, "9q8yy"),
(40.7128, -74.0060, "dr5ru"),
])
def test_known_values(lat, lon, expected):
assert encode(lat, lon, precision=5) == expected
Fixtures:
@pytest.fixture
def sample_data():
return [(37.7749, -122.4194), (40.7128, -74.0060)]
def test_batch(sample_data):
results = batch_encode(sample_data)
assert len(results) == 2
Mocking:
def test_api_call(mocker):
mocker.patch("my_lib.client.fetch", return_value={"data": []})
result = my_lib.get_data()
assert result == []
Exception testing:
def test_invalid_raises():
with pytest.raises(ValueError, match="latitude"):
encode(91.0, 0.0)
For detailed patterns, see:
- FIXTURES.md - Advanced fixture patterns
- HYPOTHESIS.md - Property-based testing
- CI.md - CI/CD test configuration
Test Principles
| Principle | Meaning |
|---|---|
| Independent | No shared state between tests |
| Deterministic | Same result every run |
| Fast | Unit tests < 100ms each |
| Focused | Test behavior, not implementation |
What ships with it
3 files 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.
- 6d ago First seen · 119 lines · 68 tokens per session scan A 023f8e373cc1
testing-python-libraries is a skill published in the GitHub repository CHENyiru3/AI-Skills-Collections (1 stars, last pushed 7d ago), licensed MIT. It adds 68 tokens to every session and 893 once invoked, about $0.0003 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 2026-10-02.
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