Content
78%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, domain-dense skill body with a clear workflow, real runnable scripts, and exemplary progressive disclosure into a complete, verified bundle. Remaining gaps are the absence of example invocations with actual arguments, no explicit error-recovery loops, and some repetition of the safety boundary.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense, domain-specific guidance with no padding of concepts Claude already knows (e.g., it never explains what GRADE or survival analysis is), but the hard-safety boundary is restated across the Data Gate, artifact-header, and per-domain sections, which could be consolidated. Efficient with minor trimmable repetition — 4, not 5. | 4 / 5 |
Actionability | Provides a concrete Need→Asset→Script table, runnable commands ("python3 scripts/validate_cds_artifact.py --help"), executable verification commands, and a required-header checklist. Not a 5 because no example invocation with real arguments is shown, only --help listings. | 4 / 5 |
Workflow Clarity | A clear four-step sequence (Frame → Select artifact → Run locally → Human review) with a pre-script Data Gate checkpoint and a dedicated Verification section ("python3 -m unittest discover -s tests/clinical-decision-support..."), so the batch-operation cap does not apply. Not a 5 because explicit error-recovery feedback loops ('if validation fails, fix and re-run') are absent. | 4 / 5 |
Progressive Disclosure | The body is a well-organized overview with per-section pointers ("See references/evidence_profiles.md") and a complete Reference Map annotating all twelve reference files; the asset/script table maps every workflow need to a real bundle file, and all referenced paths exist. References are one level deep and clearly signaled. | 5 / 5 |
Total | 17 / 20 Passed |