Content
71%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 exemplary in conciseness and progressive disclosure for a simple stub skill, but it provides no in-body executable guidance, relying entirely on the entrypoint and bundle script for actionability.
Suggestions
Add a one-line runnable example mirroring the entrypoint (e.g. `python scripts/plot.py paper/results.csv --out paper/figure_1.pdf`) so the body is actionable without inspecting frontmatter.
Mention the expected CSV header (x, y_baseline, y_ours) as a quick validation hint so missing columns fail fast.
Optionally note that the script prints 'wrote <path>' on success as a lightweight verification checkpoint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Two lean sentences state the I/O contract and the matplotlib runtime dependency with zero padding or explanation of concepts Claude already knows, matching the 'lean and efficient; every token earns its place' anchor. | 5 / 5 |
Actionability | The body only describes the action ('Reads a CSV... and writes a two-line plot as PDF') with no executable code or commands inline; concrete execution lives in the entrypoint and scripts/plot.py, leaving the body itself at the 'high-level hints, missing specific steps' anchor. | 2 / 5 |
Workflow Clarity | The single action (CSV in, PDF out) is unambiguous, benefiting from the simple-skill exception, but there is no verification checkpoint that the PDF was produced or that expected columns exist, keeping it just below 5. | 4 / 5 |
Progressive Disclosure | The body is under 50 lines and well-organized, with the executable logic correctly split into scripts/plot.py (confirmed present and referenced via the entrypoint), fitting the 'simple skill, well-organized sections' exception for a top score. | 5 / 5 |
Total | 16 / 20 Passed |