Skills

Store Signals

Close the post-launch loop, turn a live app's App Store signals (reviews, analytics...

Install

npx skills add rshankras/claude-code-apple-skills --skill store-signals -g -a claude-code -y
Category
Mobile
Updated
3mo ago
License
MIT
Context cost
Lightabout 1,173 tokens
Runs scripts
No, instructions only

What it does

Close the post-launch loop, turn a live app's App Store signals (reviews, analytics, sales, crashes, listing conversion) into a metric-tagged backlog for the next version, AND verify whether last cycle's changes moved the metric they promised to move. Read-only on App Store Connect; every change is surfaced and routed to another command, never auto-applied. Use before planning the next version, on a monthly cadence, or ~1-2 weeks after shipping to check if a change worked.

Store Signals

Pull what the shipped app is actually telling you and convert it into the next backlog, then verify whether last cycle's bets paid off.

This is the missing arc that turns build → ship into a loop: ship → MEASURE → DIAGNOSE → next PLAN → build → ship → measure again… The ledger (SIGNALS.md) is what makes it a loop and not a monthly report.

Where it fits (read the seams)

  • Not analytics-interpretation. That interprets a metric you hand it (is 14% D7 good?). This is the end-to-end operate loop: gather every signal → cluster → diagnose → write a metric-tagged backlog → close last cycle's hypotheses. It uses analytics-interpretation's benchmarks.
  • Read-only on ASC. Never responds to reviews, never mutates metadata/pricing. It surfaces, gates on explicit OK, and routes the change to the right command (next-version, bugfix, metadata).
  • Feeds planning. Output is a dated backlog appended to ROADMAP.md + rows in SIGNALS.md, consumed by /apple:next-version / /apple:release.

Prerequisites

  • A live (or TestFlight) app; resolve its appId from .planning/STATE.md, else list_apps + confirm.
  • .planning/ context: STATE.md, APP.md, POSITIONING.md (job-to-be-done + guardrails).
  • .planning/SIGNALS.md if present, the OPEN hypotheses from prior runs (each with a target metric, recorded baseline, and "check-after" date). See signals-ledger.md for the ledger + backlog formats.

Flow

Read the whole SKILL.md on GitHub

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