Content
42%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.
The body is a well-sectioned but verbose feature catalog that explains basic statistics Claude already knows and inlines long report templates, with no executable workflow or split-out reference files.
Suggestions
Remove or condense explanations of concepts Claude already knows (linear-regression and Pearson formulas, r-value interpretation, strength thresholds, basic pace calculation).
Add an explicit numbered workflow with validation checkpoints: read data → run data-quality checks → compute analyses → detect danger signals → generate report, including a fix-and-retry loop on quality failures.
Move the three full sample reports and the algorithm/MET reference material into separate files under references/ and link to them one level deep from SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Noticeably verbose: it restates concepts Claude already knows (linear regression y=a+bx, the Pearson formula and r=±1/0 interpretation, strength thresholds, pace=duration/distance) and inlines three very long sample reports. | 2 / 5 |
Actionability | Concrete data paths, formulas, output templates, and example invocations are provided, but there is no executable code or script and the analysis steps stay at a conceptual level. | 3 / 5 |
Workflow Clarity | Content is organized by feature rather than as a sequenced workflow; data-quality checks and danger-signal detection exist as implicit checkpoints but lack an explicit validate→fix→retry loop. | 3 / 5 |
Progressive Disclosure | Section headers give reasonable structure, but the ~430-line file is monolithic with no bundle references and inlines content (sample reports, algorithm explanations, MET table) that could live in separate files. | 3 / 5 |
Total | 11 / 20 Passed |