Content
80%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, concise instruction skill with concrete templates and examples. Its main weakness is workflow clarity: the experiment lifecycle and ship/revert decisions lack explicit validation checkpoints and feedback loops.
Suggestions
Add an explicit validation checkpoint before analysis (e.g., 'Confirm the test has reached the agreed sample size AND no guardrail metric was breached before interpreting results').
Provide the actual sample-size formula or a named method (e.g., two-proportion z-test power calculation) rather than only stating 'Estimate sample size'.
Include an error-recovery feedback loop for the analyze/decide step (e.g., if guardrails are violated → revert; if underpowered → continue testing rather than ship).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean — a tight Overview, an 8-step workflow, the ICE pattern, and concrete example prompts — assuming Claude's competence without explaining statistics concepts it already knows. | 5 / 5 |
Actionability | Provides a concrete hypothesis template, ICE definitions, and implementation checklist items, but 'Estimate sample size' omits the actual formula/method, leaving a minor gap in executable detail. | 4 / 5 |
Workflow Clarity | An 8-step sequence is present with pre-launch decision rules, but validation checkpoints for consequential ship/revert decisions are only implicit (e.g., 'after the test reaches the agreed sample size') with no error-recovery feedback loop. | 3 / 5 |
Progressive Disclosure | Under 50 lines with no need for external references, organized into clear sections (Overview/Workflow/Backlog/Examples), satisfying the simple-skill exception for a top score. | 5 / 5 |
Total | 17 / 20 Passed |