Content
81%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 highly actionable, well-sequenced instruction-only skill: concrete templates, worked examples, decision tables, and explicit validation checkpoints make the workflow executable end to end, with a cleanly signaled external reference. Its main weakness is token efficiency — a statistics-primer section that re-teaches known concepts and a failure-patterns list that duplicates the test-setup mistakes.
Suggestions
Trim or externalize the 'Statistical foundations' section: Claude already knows what a 95% significance level means, peeking bias, and Bonferroni correction — keep only the CRO-specific judgment calls (e.g., the sample-size quick-reference table and the 'iterate via design and qualitative research instead' decision rule) and move the primer to a reference file if it must be kept.
Merge 'Failure patterns' with 'Common test setup mistakes' — peeking/early stopping, atypical periods, and underpowered tests appear in both lists; a single consolidated list removes the duplication without losing content.
Consider moving the sample-size reference table and output-format template into a references file alongside hypothesis-library.md so SKILL.md reads as the framework overview with one-level-deep detail files.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Most of the body is lean, domain-specific guidance, but the "Statistical foundations" section re-teaches concepts Claude already knows ("A 95% significance level means: if there were truly no difference between variants, there's only a 5% chance...", peeking bias, Bonferroni), and "Failure patterns" substantially duplicates "Common test setup mistakes" (peeking, early stopping, atypical periods, underpowered tests). These are more than minor instances of over-explanation, keeping it below 4, while the bulk of the framework content earns its tokens, keeping it above 2. | 3 / 5 |
Actionability | Guidance is fully concrete throughout: a hypothesis template with a worked example, ICE/PIE scoring ("Score each 1 to 10"), a pre-launch parameters checklist, a decision framework table with explicit thresholds (">95% significance, exceeds minimum effect"), a sample-size quick-reference table, and a copy-paste-ready markdown output template. Per the rubric's instruction-only note, the absence of code is not penalized when guidance is this actionable. | 5 / 5 |
Workflow Clarity | The 10-step workflow over the 4-phase framework is clearly sequenced with explicit validation checkpoints: "QA carefully (broken variants invalidate tests)", "Don't peek. Don't stop early", pre-defined ship/kill/extend decision criteria, and guardrail metrics. Feedback loops for error recovery are explicit ("Kill. Capture the lesson. Iterate hypothesis" and "Compound. Apply lessons to next round of hypotheses"), matching the top anchor. | 5 / 5 |
Progressive Disclosure | Structure is good: the hypothesis pattern library is correctly externalized to a verified one-level-deep reference ("references/hypothesis-library.md - Common high-impact hypothesis patterns by funnel stage") that exists in the bundle and is clearly signaled. However, the ~270-line body inlines the statistics primer and sample-size table — content that could be split out the same way the hypothesis library was — representing the minor organization gaps of the 4 anchor rather than the fully appropriate split of 5. | 4 / 5 |
Total | 17 / 20 Passed |