Mostly efficient and rich in non-obvious domain facts (3 prompts/year, per-version reset, throttle behavior), but the "Why Ratings Matter for ASO" opening explains fairly self-evident points ("higher ratings rank better", "a 4.8 beats 4.2 at a glance") that could be tightened.

Provides fully executable Swift (SKStoreReviewController) and Kotlin (ReviewManager) code, concrete session-based gating criteria, a good/bad prompt-moment table, a pre-prompt survey template, and a copy-paste output format — all specific and actionable.

The recovery process is clearly sequenced (Diagnosis steps + a Day 0/1-3/7/8+/Week 3 timeline) with a monitoring checkpoint ("Monitor rating trend"), and the timing framework gives an explicit gating checklist.

Well-organized into clear sections with a Related Skills pointer, but it is a single monolithic file (no bundle files present) over 50 lines with all detail inline and no one-level-deep references, fitting the "content that should be separate is inline" anchor rather than the reference-split 3 anchor.

Lists multiple concrete actions — "improve their app's star rating", "increase ratings volume", "optimize when and how they prompt users for a review", "recover from a bad rating period" — matching the anchor for multiple specific concrete actions.

Explicitly answers both what it does and when to use it, with a clear "Use when the user mentions..." trigger clause; not capped at 2 because the when-guidance is explicit.

Broad coverage of natural phrasings users would say ("app rating", "star rating", "ask for review", "low rating", "rating drop", "get more reviews", "recover from 1-star") plus technical triggers ("SKStoreReviewRequest", "In-App Review API").

Clear niche (review-prompt timing/strategy) with distinct triggers, and explicitly disambiguates from adjacent skills ("For responding to reviews, see review-management. For overall ASO health, see aso-audit."), so unlikely to trigger the wrong skill.