App discovery
ASO & app-market research skills for AI agents — Claude Code, Cursor, and any MCP client. Install: npx skills add getappniche/aso-skills
npx -y skills add getappniche/aso-skills --skill app-discoveryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 12 days oldThe repository was created 12 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Scan an App Store or Google Play category or niche and produce a shortlist of apps worth studying, with revenue and download data. Use when the user wants to find apps in a space, size a niche, find underserved segments, or build a research candidate list.
SKILL.md
3.3 KB, as published. Nobody here has run it
App Discovery
Turn a vague market question ("what's out there in sleep tracking?") into a concrete, data-backed shortlist.
Requirements
Works best with the GetAppNiche MCP server connected (search_apps, get_app_detail).
Without it, fall back to reasoning from public store pages and say so explicitly.
Workflow
-
Frame the niche as filters, not just words. Restate the request as (a) a store —
apple,google, or both; (b)categoriesto include; (c) a search phrase if the niche is narrower than a category; and (d) the thesis expressed numerically.search_appstakes the whole Explore filter set, so state the thesis directly instead of fetching broadly and filtering by eye:- "who makes real money here" →
min_revenue: 10000,sort_by: "revenue" - "beatable incumbents" →
min_revenue: 10000,max_reviews: 1000 - "is this niche still being entered" →
max_days_since_release: 365 - "what's heating up" →
growth_period: "30d",growth_direction: "up",min_growth_pct: 20,sort_by: "growth" - "abandoned apps to displace" →
min_reviews: 1000, plusupdated_beforea year ago - "non-US opportunity" →
languages: ["de", "ja"]
Confirm only if genuinely ambiguous.
- "who makes real money here" →
-
Run two or three sharp queries, not ten scattershot ones. One query per thesis (
limit: 25is a good default). Because the filters do the narrowing, a second query should test a different hypothesis — not a synonym of the first. -
Deduplicate and rank. Merge results, then rank by whatever signal matches the user's goal.
sort_byacceptsdownloads,revenue,growth,reviews,rating,title,releasedandupdated, so let the query do the sorting. -
Deepen the top candidates. For the top 5–8 apps, call
get_app_detailto pull ratings, review counts, and metadata before making claims about any single app. It accepts the canonical id (apple:284882215,google:com.example.app), a bare Apple track id, an Android package name, or a store URL pasted straight from a browser. -
Summarize the niche. Close with 2–3 sentences on the shape of the market: concentration (one winner vs. long tail), price patterns, and obvious gaps.
Output
A table — App · Store · Downloads/mo · Revenue/mo · Rating (count) · One-line angle — followed by the niche summary and a "worth a deeper look" pick with reasoning. State the filters you used, so the user can see what the shortlist is and isn't.
Guardrails
- Use revenue and download figures to rank and compare; round them in output rather than quoting to the dollar.
- Each call costs 1 credit. If a call reports an out-of-credits error, relay it: credits refresh monthly and can be topped up in Settings at app.getappniche.com.
- A filter combination that returns nothing is a finding ("nobody is making $50K/mo here"), not a failure — report it before loosening the filters, and say which constraint you relaxed.
- Don't invent apps to pad a thin niche — a short honest list is the finding.