test-data-generation
Use this skill at Step 5 of the v2 SOP to generate stage-isolated synthetic test fixtures (mock data) for an OpenSpec change. Outputs fixtures into mock/阶段N-<名称>/, computes fingerprints, declares synthetic-only source, and runs the fingerprint match against the real-sample fingerprint library. Chinese trigger examples: "生成测试数据", "Mock 数据生成", "Step 5", "合成 fixture", "生成 mock", "测试数据 generation". Do NOT use to sample from production, do NOT use real PHI as seed even after redaction. Success = fixtures generated, fingerprints computed, fingerprint match against real-sample library returns zero
Profile →npx skills add charliehzm/medharness --skill test-data-generation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Test Data Generation Generates fixtures the change can be tested against, with the strong invariant: **never reversible to real patients**. ## Generation modes (pick one) | Mode | When | Risk | |---|---|---| | Pure synthetic (faker-style) | Default | Low | | Schema-driven random | When distribution matters less than shape | Low | | Distribution-matched synthetic (DP) | When ML features depend on
What does the test-data-generation skill do?
Use this skill at Step 5 of the v2 SOP to generate stage-isolated synthetic test fixtures (mock data) for an OpenSpec change. Outputs fixtures into mock/阶段N-<名称>/, computes fingerprints, declares synthetic-only source, and runs the fingerprint match against the real-sample fingerprint library. Chinese trigger examples: "生成测试数据", "Mock 数据生成", "Step 5", "合成 fixture", "生成 mock", "测试数据 generation". Do NOT use to sample from production, do NOT use real PHI as seed even after redaction. Success = fixtures generated, fingerprints computed, fingerprint match against real-sample library returns zero
How do I install it?
Run `npx skills add charliehzm/medharness --skill test-data-generation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From charliehzm/medharness, a repository with 96 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.