Content
88%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 high-quality, dense instruction skill: complete templates, a well-sequenced workflow with pre-launch checklists and decision criteria, and a clearly signaled reference library. The main improvements are trimming didactic statistics explanations Claude already knows and splitting the statistical foundations material into a reference file to slim the main body.
Suggestions
Trim explanations of concepts Claude already knows in the 'Statistical foundations' section — the definition of what 95% significance means and the basics of multiple comparisons inflate tokens without adding skill-specific value; keep the caveat about Bayesian tool output ('95% chance of being best') and the misreading warning, which are domain-specific.
Move the statistical foundations material (sample-size quick-reference table, multiple-testing notes) into a references file alongside hypothesis-library.md, keeping SKILL.md focused on the workflow, decision rules, and output format.
Scope the broadest description triggers ("hypothesis", "optimization", "lift") to conversion-specific phrasings (e.g., "conversion hypothesis", "lift estimate") to reduce overlap risk with general optimization and experimentation skills.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and table-driven with no padding, but a few passages explain statistics Claude already knows — "A 95% significance level means: if there were truly no difference between variants, there's only a 5% chance you'd see results this extreme by chance" and "The more variants and metrics tested simultaneously, the more false positives" — which could be trimmed. This fits anchor 4 (efficient, minor over-explanation) rather than 3, since the overwhelming bulk is dense checklists and templates. | 4 / 5 |
Actionability | Fully actionable for an instruction-only skill: a copy-paste-ready hypothesis template with a worked example ("Because session replays show users abandoning at the shipping step..."), an ICE scoring procedure ("Score each 1 to 10"), a sample-size quick-reference table with explicit inputs, a five-outcome decision table, and a complete markdown output template covering the common cases. Stack-agnostic design is explicitly stated, justifying the absence of tool-specific commands. | 5 / 5 |
Workflow Clarity | A 10-step sequenced workflow layered over a 4-phase framework, with explicit checkpoints: pre-launch parameter checklist ("Test parameters to define before launch"), QA checkpoint ("QA carefully (broken variants invalidate tests)"), run discipline ("Don't peek. Don't stop early"), and a decision framework covering all five outcome branches including feedback loops for inconclusive results ("Larger test, different angle, or move on"). | 5 / 5 |
Progressive Disclosure | Good structure with one clearly signaled one-level-deep reference (references/hypothesis-library.md — verified real, relevant, and non-nested) and well-organized sections. However, at ~270 lines with only one reference file, inline material such as the statistical foundations section (sample-size table, multiple-testing notes) is reference-grade content kept in the main body — minor organization gaps fitting anchor 4 rather than the fully-split structure of anchor 5. | 4 / 5 |
Total | 18 / 20 Passed |