Content
87%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A concise, highly actionable skill body with concrete API calls and quantified detection rules. The only gap is the absence of a validation checkpoint in what is otherwise a well-sequenced batch scan.
Suggestions
Add a verification step before scanning, e.g. 'Confirm all pages fetched (has_more false) before grouping; if pagination incomplete, re-fetch and recount' to satisfy the batch-operation feedback-loop expectation.
Note how to handle a large memory set that approaches the 200-cap, so partial results are explicitly flagged rather than silently reported.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean ~45-line body that assumes Claude's competence — no explanation of what memories are — with every section (detection table, output format, constraints) earning its place. | 3 / 3 |
Actionability | Provides a copy-paste-ready get_memories call with explicit filters/page_size and concrete numeric detection thresholds (>60% noun overlap, confidence < 0.3, 180 days), fully executable guidance. | 3 / 3 |
Workflow Clarity | Steps 1-6 are clearly sequenced, but this is a batch operation (up to 200 memories) with no validation/verification checkpoint (e.g. confirming pagination completeness before scanning), so workflow clarity is capped at 2 per the batch-operations guideline. | 2 / 3 |
Progressive Disclosure | Under 50 lines with no need for external references, organized into clear When-to-use / Steps / Constraints sections, which satisfies the simple-skill allowance for a top score without bundle files. | 3 / 3 |
Total | 11 / 12 Passed |