aso-analysis
ASO performance for an app or collection — tracked-keyword positions and (gate-iv-gated) trends, category-rank trend, keyword opportunities with competitor context, an interactive add-keyword loop (the only write path), and honest metadata suggestions. Emits a structured findings.json plus a self-contained HTML report. Trigger on "ASO report", "keyword rankings", "keyword opportunities", "how do we rank for <keyword>", "suggest keywords to add".
Install
With your agent
Install OMGSkills skill "appfollow/appfollow-ai-toolkit:skills/aso-analysis" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/AppFollow/appfollow-ai-toolkit /tmp/appfollow-ai-toolkit && ln -s /tmp/appfollow-ai-toolkit/skills/aso-analysis ~/.claude/skills/aso-analysisFrom README
aso-analysis Read using-appfollow first (session, write ritual, error codes). Inputs scope: app, whole collection, or a user-chosen subset of apps from one collection (e.g. "just these 3 apps from my "). For a subset: resolve the collection via listcollections, list its apps via listapps, then gather ASO data for only the chosen apps — emit scope.type: "collectionsubset" with collectionname set and apps = the chosen subset (not the full collection). Spanning multiple collections in one report is not supported yet (deferred). countries: default 1 primary. devices: App Store → iphone, ipad; Google Play → android. keyword seeds (optional). Default depth Estimate ≈ A×C×D×[S×P×12 (listkeywords) + S×12 (getrankings)] + A×C×[Kseed×12 (suggestions) + Kserp×12 (search)] + A(as)×12 (searchads) + A×12 (aso report, optional). Default = deep: max S=4 trend sample-dates (today / −7d / −14d / −28d), max Kserp=10.