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growth-analysis

Skill1 starsChanged 46 days agoMITView on GitHub

Explain how an app grew or declined over a period, using ASOSpy installs, revenue, ratings and chart-rank history, and find likely causes in reviews and release dates. Use when the user asks why an app's downloads, revenue or rank changed, or wants a growth timeline. Needs the ASOSpy MCP server.

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    1. AppKittie/aso-mcp-skills★ 8same name
    2. Nirusan/claude-config★ 7same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

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SKILL.md

Growth analysis

When to use

  • "Why did X's downloads drop last month?", "how has X grown this year?", "when did X take off?".
  • To check whether a launch, a price change or an update moved the numbers.

Inputs

InputDefaultNotes
ApprequiredAny identifier (id, store URL, ASOSpy URL, name).
Periodlast 90 daysdate_from / date_to as YYYY-MM-DD, at most 366 days per call.
CountryusFor chart ranks only.

Tools

get_app_detail, get_app_historicals (metrics: installs, revenue, ratings, reviews, score), get_store_ranking_history, get_app_reviews.

Workflow

  1. get_app_detail: current numbers, release date, last update, version.
  2. get_app_historicals with metrics: ["installs", "revenue", "ratings", "score"] and the period. For more than 366 days, make one call per year-sized window.
  3. get_store_ranking_history for the same period and country.
  4. Find change points: days where daily installs, revenue or rank moved sharply and stayed moved (ignore one-day spikes).
  5. get_app_reviews with sort: "most_recent" (add sort: "lowest_rated" if the rating fell) and read the reviews around each change point.
  6. Link each change point to evidence: an update (updatedAt, versions in reviews), a rating change, a chart move, or complaints.

Output

  1. The overall trend in one paragraph: start value, end value, change in %.
  2. A dated list of change points: date, metric, size of the change, likely cause, evidence.
  3. Mark every cause as a hypothesis unless a review or detail field shows it directly.

Limitations

  • iOS installs and all revenue are ASOSpy estimates. The shape of the curve is more reliable than single days.
  • Revenue can be missing for some days or months (no estimate); do not read gaps as zero.
  • iOS ratings, reviews and score history come from the app's main storefront. Google Play review history is one storefront too.
  • There is no data on marketing spend, featuring or press, so name these only as possibilities.

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