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.
The body is concise and highly actionable with executable examples throughout, but workflow clarity is capped by the absence of explicit validation/retry checkpoints for rate-limited network operations, and a small amount of reference material is inlined that could live in a separate file.
Suggestions
Add an explicit validation/feedback loop for network failures: on rate-limit or timeout, reduce -n or wait, then re-run — sequence it as numbered steps with a retry-until-success checkpoint to raise workflow_clarity.
Move the full parameter table and search-operator list into a one-level-deep reference file (e.g. references/REFERENCE.md) with a short pointer in SKILL.md to improve progressive_disclosure.
Include a quick 'verify the package installed' or sample-output check step so Claude can confirm the script ran successfully before formatting results.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient with no over-explanation of concepts Claude already knows; every section (workflow, parameters, examples, operators, errors) earns its place. | 5 / 5 |
Actionability | Provides fully executable, copy-paste-ready python3 commands with concrete flags and worked examples covering text, news, image, and file-output cases. | 5 / 5 |
Workflow Clarity | A clear 3-step sequence (judge type → run script → format results) is present, but there is no explicit validation checkpoint or fix-and-retry feedback loop for the network/rate-limit operations; a static error list does not constitute a feedback loop. | 3 / 5 |
Progressive Disclosure | Well-organized sections with a single bundled script and clear param table; minor gap is that the full parameter table and search-operator reference are inlined rather than split into a one-level-deep reference file. | 4 / 5 |
Total | 17 / 20 Passed |