Content
83%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 strong, actionable skill body with a complete executable example, well-signaled one-level-deep references, and clear batch/error constraints. The only gap is the absence of an explicit validation/retry feedback loop for the batch operations it recommends.
Suggestions
Add an explicit validate-then-retry loop for batch operations (e.g., on non-200 or partial results: chunk, retry with backoff, re-check) to satisfy the feedback-loop expectation for batch/destructive workflows.
Trim the duplicated function descriptions between 'Key Features' and 'Implementation Details' to tighten token efficiency.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is well-organized and assumes Claude's competence without explaining what KEGG or REST APIs are; a few API-to-function descriptions restate endpoint behavior that could be trimmed, but most tokens earn their place. | 4 / 5 |
Actionability | It provides a fully executable end-to-end example with real function names, identifiers, and parsing logic, plus a detailed API-to-function mapping with concrete option values and batching limits. | 5 / 5 |
Workflow Clarity | The example sequences find -> link -> get -> convert with inline validation, and practical constraints cover chunking and HTTP failures, but there is no explicit validate-then-fix retry loop for the batch operations the skill explicitly encourages. | 4 / 5 |
Progressive Disclosure | The SKILL.md is a clear overview that delegates bulk detail to a real one-level-deep reference (references/kegg_reference.md) and a real script (scripts/kegg_api.py), both referenced explicitly, with appropriate inline structure and navigation. | 5 / 5 |
Total | 18 / 20 Passed |