Content
88%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 high-quality, executable scientific skill body with concrete code, a sequenced workflow, an explicit numbering-verification checkpoint, and honest limitations. It is concise and actionable, with only minor verbosity and no bundled reference files to split out.
Suggestions
Move the interpretation table and cross-references into a reference file to improve progressive disclosure and keep SKILL.md a lean overview.
Trim the opening paragraph that restates the description verbatim.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Largely lean with executable code blocks and tables that assume domain competence; a few phrases like 'This is the annotation track that anchors...' repeat the description and could be trimmed. | 4 / 5 |
Actionability | Provides copy-paste-ready, fully executable Python calls with realistic arguments, concrete return schemas, and specific downstream snippets (e.g. the by_pos indexing pattern) covering common cases. | 5 / 5 |
Workflow Clarity | Clearly sequenced 5-step workflow with an explicit verification checkpoint (Step 3 landmark assertion), an error-recovery instruction ('Do not silently rebase positions'), and an honest-limitations section covering fragile numbering. | 5 / 5 |
Progressive Disclosure | Well-organized sections with a clean cross-reference table of related tools at one level deep, but all content is inlined in SKILL.md with no separate reference files; minor organization is strong but external split is absent. | 4 / 5 |
Total | 18 / 20 Passed |