Content
82%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 dense, actionable advisory skill with concrete formulas, templates, and checklists. Slightly verbose in advisory sections and lacks explicit error-recovery feedback loops.
Suggestions
Tighten the 'Is a Referral Program Right for You' section — collapse the table into a single concise fit/weak-fit heuristic to reduce advisory padding.
Add an explicit validate→fix→retry loop for the launch checklist (e.g., 'if reward issuance test fails, re-instrument events and re-test end-to-end').
Consider moving the detailed reward-pattern and fraud-mitigation tables into a references/ file, leaving SKILL.md as a lean overview with one-level-deep pointers.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Table-driven and assumes Claude's competence without explaining what a referral program is, but advisory sections like 'Is a Referral Program Right for You' add a little non-essential padding. | 4 / 5 |
Actionability | Provides a concrete sizing formula, K-factor formula, specific default reward ranges, named tools/MMPs, a copy-paste output template, and an instrumented analytics event list — fully actionable for an advisory skill. | 5 / 5 |
Workflow Clarity | Clear sequenced flow from assessment through output with a launch-checklist containing validation items, but lacks explicit validate→fix→retry feedback loops that would warrant a 5. | 4 / 5 |
Progressive Disclosure | Single well-organized SKILL.md with clear section headers and one-level-deep, clearly signaled cross-skill handoffs; no nested references, though a few detailed tables could optionally live in separate reference files. | 4 / 5 |
Total | 17 / 20 Passed |