Open skill · v1.0.0
Give an AI agent the store rules, not permission to guess.
A skill package for AI coding and writing agents that work on App Store and Google Play listings. It brings the current field limits, a review checklist and a validator script, and tells the agent what it must never invent or change on its own.
Six tasks
It loads only what the task needs.
- 01Audit an existing listing without changing it
- 02Draft a full metadata set from your product facts
- 03Localize with a native-review step
- 04Turn product screens into a screenshot brief
- 05Plan a store test around a decision
- 06Check launch readiness and list blockers
Install
Works with any agent that reads skill folders.
Extract the package into your agent's skills directory, or copy the folder from GitHub. It includes the main skill file, focused references, a local listing validator and a review report template.
tar -xzf app-store-growth-v1.0.0.tgz
python3 app-store-growth/scripts/validate_listing.py listing.json
Canonical source
The complete skill file
Copy it into your agent's skills folder, or read it here first. Nothing in it calls a network service.
---
name: app-store-growth
description: Sourced App Store and Google Play listing work. Use when auditing, drafting, localizing, or validating store metadata; planning screenshots; writing experiment briefs; or reviewing launch readiness for Apple-platform and Android apps.
---
# App Store Growth
Help the user make an accurate store decision, not merely produce more copy.
## Safety and working agreement
- Treat unreleased metadata and product details as private. Do not upload them or send them to external services unless the user explicitly asks.
- Start with read-only discovery. Never change a store listing or external console without explicit confirmation of the exact change.
- Do not scan home directories, environment variables, credentials, analytics, or unrelated repositories.
- Preserve existing voice and accurate claims. Show a focused diff before overwriting files.
- Never invent search volume, rank, conversion, revenue, testimonials, competitor behavior, or platform rules.
- Label official rules, observations, hypotheses, and recommendations distinctly. Recheck volatile rules in primary documentation.
## Choose the workflow
1. Establish the product facts: product, audience, job, promise, proof, and exclusions.
2. Pick one mode:
- **audit** — compare existing listing content with the product facts and current platform rules.
- **draft** — write a coherent metadata set from supplied evidence.
- **localize** — adapt meaning and intent for a locale; do not merely translate word-for-word.
- **creative-brief** — map screenshot or video frames to a message and visible product proof.
- **experiment** — define the decision, hypothesis, controlled change, measure, guardrail, and stopping rule.
- **launch-review** — find submission blockers, missing evidence, and unverified claims.
3. Read only the relevant reference files below.
4. Return a concise review: decision summary, blocking issues, field-by-field work, assumptions, and sources to recheck.
## Reference map
- Apple metadata: `references/apple-metadata.md`
- Google Play listing: `references/google-play-listing.md`
- Localization: `references/localization.md`
- Screenshots and creative: `references/creative-briefs.md`
- Experiments: `references/experiments.md`
- Launch readiness: `references/launch-readiness.md`
- Evidence and claim labels: `references/evidence-and-claims.md`
- Portable project brief: `references/workbench-schema.md`
Use `scripts/validate_listing.py` for deterministic length and duplicate checks. It reads one local JSON file and makes no network requests. Use `assets/review-report-template.md` when a durable review report helps the user.
## Quality bar
Prefer one defensible promise over a pile of keywords. Connect every creative claim to visible product evidence. Distinguish discoverability work from conversion work. Make the next decision obvious, and say what remains uncertain.
You stay in charge
Read it, change it, and approve every store change.
The skill starts read-only, asks before any live store change, and never makes up metrics. For the prompts it is built around, see Use AI for App Store Optimization.
Also by the author: Agent skills, explained on Product Builder.