Conciseness

Lean and efficient — a compact step list, a concrete method menu, and genuine domain principles ('Measure actual behavior, not users\' opinions'); only 'Think step by step' is mild filler.

Actionability

Concrete, executable guidance: named experiment methods and a crisp output spec (Assumption/Experiment/Metric/Success threshold) with a required table format, but no worked example of a completed experiment specification.

Workflow Clarity

Clear 4-step sequence (clarify → suggest methods → apply principles → specify experiments with required fields); no validation checkpoints needed since the task is non-destructive, but nothing confirms output quality either.

Progressive Disclosure

Under 50 lines with well-organized sections (Context, Instructions, Further Reading); no bundle files are needed and the external links are clearly signaled in a dedicated section.

Specificity

Names several concrete actions ('prototypes, A/B tests, spikes'), but the trailing 'and other low-effort validation methods' is a catch-all rather than concrete, leaving minor gaps in coverage.

Completeness

Explicitly answers both what ('Design experiments to test assumptions... prototypes, A/B tests, spikes') and when ('Use when validating assumptions, testing feature ideas cheaply, or planning product experiments') with concrete trigger phrases.

Trigger Term Quality

Good natural keyword coverage ('validating assumptions', 'testing feature ideas cheaply', 'planning product experiments', 'A/B tests'), but a few common variations like 'hypothesis testing' or 'experiment design' are missing.

Distinctiveness Conflict Risk

Clear niche — experiment design for an existing product — with distinct triggers, but phrases like 'validating assumptions' carry minor overlap risk with adjacent product-discovery skills.