Content
87%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a concise, well-organized, and highly actionable reference of concrete figure-design specifications. Its only notable gap is the absence of a sequenced workflow with validation checkpoints, which is less applicable to a reference-style skill than to a destructive/batch process.
Suggestions
If a typical usage involves a multi-step sequence (build figure -> verify sizing/DPI -> export vector -> embed fonts), present it as an ordered workflow with an explicit verification step before export to lift workflow clarity.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence: it never explains what matplotlib or PDFs are, and every line is direct best-practice guidance with no padding, matching the top anchor. | 3 / 3 |
Actionability | It gives highly concrete, actionable specifics — exact column widths in inches/mm, 300 DPI minimums, named palettes (Okabe-Ito, viridis), an inline code snippet (`plt.subplots()` with `constrained_layout=True`), and star significance thresholds — and the rubric's instruction-only carve-out means the absence of full code blocks is not penalized when guidance is this actionable. | 3 / 3 |
Workflow Clarity | Content is well-organized into clearly labeled sections and ends with a quality checklist, but it is a reference of principles rather than a sequenced multi-step process, and it lacks explicit validation/feedback checkpoints that the top anchor expects. | 2 / 3 |
Progressive Disclosure | At 44 lines with no bundle files and no need for external references, the skill qualifies for the under-50-lines carve-out, and its well-organized sections satisfy the top anchor without requiring file references. | 3 / 3 |
Total | 11 / 12 Passed |