Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured reference skill body: concrete steps, a worked example, a clearly signalled one-level-deep catalog reference, and a clean ordered workflow. Its only weakness is mild verbosity from the worked example re-enumerating the dimension table.
Suggestions
Shorten the worked checkout example or reference the dimension table instead of re-listing all ten letters, to reduce token redundancy.
Consolidate the three references to references/dimensions-catalog.md into one clearly signalled pointer to avoid repetition.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body avoids explaining concepts Claude already knows, but the long worked checkout example substantially re-enumerates the ten dimensions already present in the table, and the catalog is referenced three times, so it could be tightened. | 2 / 3 |
Actionability | 'How to use' gives six concrete numbered steps and the worked example is a fully specified checkout model with real technologies (Stripe, Postgres, Redis, SendGrid), providing concrete, specific, actionable guidance for this reference skill. | 3 / 3 |
Workflow Clarity | A clear six-step ordered sequence is present with an explicit checkpoint ('Flag the unknowns. Any letter you can't fill is a gap to investigate'); as a non-destructive modelling task no validate-fix-retry loop is required. | 3 / 3 |
Progressive Disclosure | The body is an overview that clearly signals a single one-level-deep reference (references/dimensions-catalog.md, a real file, linked in three places) and keeps detailed per-letter prompts offloaded rather than inline. | 3 / 3 |
Total | 11 / 12 Passed |