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使用 pytest、TDD 方法论、测试夹具（Fixtures）、模拟（Mocking）、参数化（Parametrization）以及覆盖率要求的 Python 测试策略。
Passed 21 of 22 test cases with the skill, and 21 of 22 without it.
1 fixed20 passed either way0 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
We are setting up test coverage enforcement for our Python backend service using coverage tools. The team is debating whether to require 100% test coverage across the entire codebase or settle for 50%. What general baseline coverage percentage should we target for the overall codebase, and what coverage should be mandated for critical paths?
| Checked | Without skill | With skill |
|---|---|---|
| The response recommends at least an 80% coverage target for the overall codebase. | Passed | Passed |
| The response mandates 100% coverage for critical paths. | Missed | Passed |
The instructions your model reads when the skill loads.
使用 pytest、TDD 方法论和最佳实践的 Python 应用程序全面测试策略。
始终遵循 TDD 循环：
# 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)
pytest --cov 来测量覆盖率test cases passed, vs 21 / 22 without
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