Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
An exemplary skill body: concise, fully actionable, with a clear routing workflow and appropriately split-out detail in a real bundle script.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and action-dense with no prose padding: commands, compact reference tables, and targeted gotchas; assumes Claude's competence without explaining what a ROC curve or AUC is in narrative form. | 3 / 3 |
Actionability | Fully executable, copy-paste-ready invocations throughout — `tu run Epidemiology_diagnostic '{...}'`, `ROC_analysis(scores=[...], labels=[...])`, `python skills/.../scripts/roc_analysis.py --input scores.csv`, and `tu run Epidemiology_bayesian '{...}'`. | 3 / 3 |
Workflow Clarity | A "Which case are you in?" routing table funnels into sequenced Steps 1–3 with explicit cross-links ("Once you choose a cutoff, build its 2×2 and run Step 1") and a held-out-validation gotcha; not a batch/destructive task so no validate-fix-retry loop is required. | 3 / 3 |
Progressive Disclosure | Well-organized overview with a one-level-deep, clearly-signaled bundle reference (scripts/roc_analysis.py, verified present on disk) and a Related-skills section; no nested reference chains. | 3 / 3 |
Total | 12 / 12 Passed |