App Store Review Digest

Star ratings tell you that people are unhappy, not why. This pulls an app's App Store reviews straight from Apple's public feed and tags each one with what it's actually about — crashes, pricing, missing features, customer support — so you can see what's driving the rating without reading every review by hand.

What it does

1. Resolves each app you give it — a name or a numeric App Store ID — to its App Store listing.
2. Pulls recent reviews from Apple's public customer-reviews feed, up to the page limit you set.
3. Tags each review with the themes it touches on: crashes, bugs, performance, pricing, ads, login, sync, UI/design, customer support, missing features, notifications, and more.
4. Buckets each review negative / neutral / positive by its star rating.
5. Ranks the app's most common complaint themes across its 1–3 star reviews.
6. Drops anything outside your rating range before billing.

This is keyword-based theme tagging, not LLM sentiment analysis — it's fast, free to run, and transparent about what matched, but it won't catch sarcasm or nuance the way a model would.

Output

Every review row carries the app-level rollup alongside it, so you don't need a second query to get the big picture:

Field	Notes
appName, rating, sentiment, title, content	The review itself
themes	Keyword-matched topics this specific review touches
appAverageRating, appReviewsAnalyzed	This app's rollup across everything fetched this run
appTopComplaintThemes	This app's most common complaint themes among 1–3★ reviews

Input

Only apps is required — names or numeric IDs, either works.

{
  "apps": ["Notion", "1232780281"],
  "country": "us",
  "maxPages": 5,
  "minRating": 1,
  "maxRating": 3
}

Set minRating/maxRating to 1–3 to pull nothing but complaints, or leave the full 1–5 range to see praise themes too.

Pricing

Pay per event. You're billed per review returned and once per app digested, not for pages fetched that came back empty.