Content
75%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-organized, mostly lean skill with one fully executable code example and clearly sequenced workflows validated by a review checklist. The main gaps are the absence of error-recovery guidance and concrete request examples for the TSDR and assignment workflows, plus an inline code block that would fit better in a bundle file.
Suggestions
Add a short error-recovery loop for the API workflows (e.g. on 429/5xx: back off and retry, on schema mismatch: re-check the live docs) to strengthen validation checkpoints.
Add a minimal concrete TSDR request example (endpoint + header) so that workflow is as executable as the PatentSearch one.
Move the full Python request skeleton into a references/ file and keep a one-line pointer in SKILL.md to slim the overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean: numbered workflows, a compact code skeleton, and no padding explaining what patents or APIs are. Minor trimming is possible — the opening paragraph restates the frontmatter description, and phrases like 'Use secondary sources only as convenience indexes' could be tightened. Not 5 because of this small redundancy; not 3 because nothing explains concepts Claude already knows. | 4 / 5 |
Actionability | The PatentSearch section includes complete, executable Python (auth header, timeout, raise_for_status) with a concrete payload. The TSDR, file-wrapper, and assignment workflows remain instruction-level ('Check the current TSDR API instructions and required API-key header') without endpoints or request examples — minor gaps, not major ones, so 4 rather than 5. | 4 / 5 |
Workflow Clarity | Each workflow has a clear numbered sequence, a pre-run verification step ('Before reusing a query, verify current endpoint names, field paths, request parameters'), and a closing Review Checklist acting as a validation checkpoint. However there are no explicit error-recovery feedback loops (e.g. what to do on a 429 rate-limit or failed query), which keeps it below 5. | 4 / 5 |
Progressive Disclosure | No bundle files exist; the single SKILL.md is well-sectioned with clear headers and external URL references clearly labeled in a References section. The ~170-line body inlines a full Python request skeleton that could live in a references/ file, which is a minor organization gap rather than a structural problem. | 4 / 5 |
Total | 16 / 20 Passed |