Content
81%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.
A well-structured, highly actionable instruction skill: concrete templates, placeholder conventions, per-figure-type requirements, and a validation checklist make the workflow unambiguous. Its weaknesses are moderate redundancy (the fabrication rule and self-containment principle are each repeated several times, and 'When to Use' duplicates the description) and an orphaned bundle script that the body never mentions.
Suggestions
Consolidate the no-fabrication guidance into one place: keep the Hard Rules (or Placeholder Convention) section and remove the repeated restatements in Input Validation, Step 1, and the blockquote.
Trim or remove the 'When to Use' section since it restates the frontmatter description almost verbatim, and drop the blockquote line that adds no new instruction.
Either reference scripts/main.py from the body (e.g., in a Usage section) or remove it from the bundle so every bundle file is discoverable from SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The figure-type element table, placeholder syntax, and legend structure template are non-obvious domain knowledge that earns their tokens, but the no-fabrication rule is restated roughly four times (Input Validation out-of-scope, Step 1's 'insert explicit placeholders rather than inventing them', the Placeholder Convention section, and Hard Rules), 'When to Use' duplicates the frontmatter description, and the blockquote ('Figure Legend Generator writes the legend text…') adds little. Mostly efficient but with several redundant sections that could be consolidated — between anchors 3 and 4, closer to 3. | 3 / 5 |
Actionability | For an instruction-only skill the guidance is fully concrete: a copy-paste-ready legend structure template, a multi-panel format, exact placeholder syntax ('[AUTHOR: specify error bar type — SEM or SD]', '[n = X per group]'), exact significance notation, and a per-figure-type table covering all common scientific figure cases. | 5 / 5 |
Workflow Clarity | The Core Workflow is a clear three-step sequence (identify details → write legend → quality check) with an explicit 7-item validation checklist and a defined handling path for missing data (use placeholders, never invent). This is a writing task, not a destructive or batch operation, so the validation cap does not apply; the checklist serves as an explicit validation step. | 5 / 5 |
Progressive Disclosure | The References section clearly signals two one-level-deep files that both exist (references/legend_templates.md, references/academic_style_guide.md), and the core working material (elements table, workflow) is appropriately kept inline. However, the bundle contains scripts/main.py, which is never referenced or navigated from the body — a minor organization gap that keeps this below the top anchor. | 4 / 5 |
Total | 17 / 20 Passed |