Content
76%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 skill body: all seven API operations are covered with executable code, real identifiers, stated limits, and a real one-level-deep reference bundle. Main gaps are the absence of validation/error checkpoints inside the batch workflows (capped at 3) and minor duplication of reference content inline.
Suggestions
Add a validation checkpoint to each workflow — e.g. in Workflow 2, check the HTTP status or empty response before iterating ('for pathway_line in pathways.split("\n"): if not pathway_line: continue' plus a status check), so batch loops fail gracefully.
Move the 'Pathway Categories' and 'Important Identifiers and Formats' sections into references/kegg_reference.md (which already has 'Pathway Classification' and 'Common Identifiers and Naming' sections), keeping only one or two inline examples.
Replace the 'Detailed Reference' bullet list with a single pointer to references/kegg_reference.md to save tokens without losing navigation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Each operation is covered leanly — 'When to use' plus a short executable snippet — with no explanation of concepts Claude already knows. Not 5 because some sections pad the token budget: 'Pathway Categories' and 'Important Identifiers and Formats' duplicate content in references/kegg_reference.md, and the 'Detailed Reference' bullet list restates what the reference file contains. | 4 / 5 |
Actionability | Every one of the seven operations gets copy-paste-ready Python with real IDs ('kegg_find("genes", "p53")', 'kegg_get("hsa05130", "json")', 'kegg_link("pathway", "hsa:10458")'), plus concrete options, limits, and output formats. Specific examples cover the common cases; nothing is pseudocode. | 5 / 5 |
Workflow Clarity | The five workflows are clearly sequenced with concrete code per step, but none embed validation checkpoints — e.g. Workflow 2 loops 'for pathway_line in pathways.split(...)' issuing one API call per pathway (a batch operation) with no status/error check or retry guidance. Per the rubric, batch workflows without validation cap workflow_clarity at 3; the separate 'Troubleshooting' section lists error meanings but does not wire them into the workflows, so this is not 4. | 3 / 5 |
Progressive Disclosure | Structure is good: quick examples per operation inline, bulk detail (full database list, all organism codes, API syntax, Biopython/Bioconductor integration) pushed to references/kegg_reference.md with clear signals ('Reference references/kegg_reference.md for detailed pathway lists', a 'Detailed Reference' section) — both bundle files verified to exist and only one level deep. Not 5 because 'Pathway Categories' and 'Important Identifiers and Formats' re-inline material the reference file already carries, a minor placement gap. | 4 / 5 |
Total | 16 / 20 Passed |