Content
93%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.
An efficient, actionable skill body with copy-paste-ready commands, a clear workflow, and exemplary progressive disclosure into a real reference file. The only gap is the absence of an explicit validation checkpoint in the workflow, though the workflow is non-destructive.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and well-organized — input format, three workflow steps with commands, options table, output tree, and a one-line dependency list — with no padding and no explanation of concepts Claude already knows, matching the score-5 anchor 'every token earns its place'. | 5 / 5 |
Actionability | Provides copy-paste-ready executable commands (`python scripts/diagnose.py data.csv --output-dir results/`), concrete option flags with defaults, and a full output-file tree, covering the common cases fully and matching the score-5 anchor. | 5 / 5 |
Workflow Clarity | A clear three-step sequence with an explicit coordination checkpoint ('Run after diagnose.py to ensure ACF/PACF plots are synchronized with stationarity results'), but it lacks an explicit validate/verify-then-proceed feedback loop; not a 5 because no validation step is present, though the destructive/batch cap does not apply since the workflow is read-only analysis. | 4 / 5 |
Progressive Disclosure | Body is an overview that clearly signals a single one-level-deep reference (`See references/interpretation.md for guidance on:`) to a real file, with bulk interpretation material split out and scripts located in `scripts/`, matching the score-5 anchor for well-signaled one-level references. | 5 / 5 |
Total | 19 / 20 Passed |