Content
78%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-structured advisory skill with excellent progressive disclosure and highly actionable, situation-mapped guidance. Its main weakness is token efficiency: it re-explains famous biases Claude already knows and repeats the same models across three overlapping tables.
Suggestions
Cut the definitional clauses from the 'Most-Used Models' section (e.g., 'People feel losses 2x more than gains') and keep only the application directive — Claude already knows these principles and the catalog covers definitions.
Consolidate the three overlapping model listings (Categories at a Glance, Most-Used Models, Quick Reference) into at most two views so the same models are not repeated three times in the body.
Make the output-verification workflow actionable: specify how to perform 'source attribution' and 'assumption audit' for recommendations, or tie each recommendation to a concrete on-page element with a confidence tag.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body defines well-known concepts Claude already knows ("Loss Aversion — People feel losses 2x more than gains", "Social Proof — People follow others") and maintains three overlapping model listings (Categories at a Glance, Most-Used Models, and the Quick Reference table all repeat Loss Aversion, Social Proof, Anchoring, etc.). It is mostly tight and table-driven, matching anchor 3 ("some unnecessary explanation or could be tightened") rather than 4 because the redundant listings span roughly 40 lines. | 3 / 5 |
Actionability | Directives are concrete and executable: "Show higher price first, then your price", "Under $100: show % discount. Over $100: show $ discount", "Limit to 3 tiers", "Let people 'own' something before paying (free trial, saved progress)", and the Quick Reference table maps common situations to specific models. As an instruction-only skill the absence of code is not penalized since the guidance is specific and covers the common marketing cases. | 5 / 5 |
Workflow Clarity | Three clearly defined entry modes (Diagnose/Apply/Reference), a five-question diagnostic sequence, and an output-artifacts table give a clear path, and the Communication section adds output verification tagging. It falls short of anchor 5 because there is no explicit end-to-end sequence or error-recovery/feedback loop; no destructive or batch operations exist, so the validation cap does not apply. | 4 / 5 |
Progressive Disclosure | The body is an overview (category table plus most-used models) that delegates the full catalog to a well-signaled one-level-deep reference with explicit load-when guidance ("The full catalog lives in [references/mental-models-catalog.md]... Load it when you need to look up specific models"). The bundle was verified: a single real catalog file exists with no nested references. | 5 / 5 |
Total | 17 / 20 Passed |