Content
73%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 strong, actionable interactive workflow with clear sequencing and built-in validation, scoring well on actionability and workflow clarity. Its main weakness is conciseness — the length and some redundant explanation could be trimmed.
Suggestions
Collapse the duplicated skill-type definitions (prose in Key Concepts vs. the decision-criteria list) into a single source of truth to cut ~20-30 lines.
Consider moving the full Q1-Q5 question scripts into a references/ file and keeping SKILL.md as an overview with the decision logic, since the inline scripts are the bulk of the length.
Trim agent notes and re-explanations of concepts Claude already understands (e.g., what kebab-case is) to improve token efficiency.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and well-structured, but at ~325 lines it re-explains material Claude already knows (e.g., the three skill-type definitions appear in both prose and table form) and could be tightened. | 3 / 5 |
Actionability | Provides copy-ready question scripts, numbered response options, and a draft-generation checklist with concrete validation commands (check-skill-metadata.py, check-skill-triggers.py, test-a-skill.sh); minor gaps only. | 4 / 5 |
Workflow Clarity | A clear sequenced flow (Step 0 → Q1/5–Q5/5 → Draft Generation) with progress labels and an explicit validation checklist plus feedback loop (run validation, fix, re-run) before declaring done. | 5 / 5 |
Progressive Disclosure | Sections are well organized (Purpose, Input, Key Concepts, Application, Examples, Pitfalls, References) with one-level-deep skill links, but no bundle files exist and some long inline content (full question scripts, decision tables) could be externalized. | 4 / 5 |
Total | 16 / 20 Passed |