Open skill · v1.0.0

Give an AI the workflow—not permission to guess.

An inspectable operating system for better app-store work: primary sources first, product truth before keywords, narrow permissions, and a human-approved diff.

Six modes

One small router. Only the context the task needs.

  1. 01Audit an existing listing without overwriting it
  2. 02Draft a coherent metadata set from product truth
  3. 03Localize intent with a native-review gate
  4. 04Turn product evidence into a creative brief
  5. 05Frame a store experiment around a decision
  6. 06Review launch readiness and source blockers

Install

Portable by design.

Download and extract the package into a skills directory supported by your agent, or copy the public folder from GitHub. The package includes the core skill, focused references, a deterministic local 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

Read the raw SKILL.md
---
name: app-store-growth
description: Evidence-aware 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 product truth: product, audience, job, promise, proof, and exclusions.
2. Pick one mode:
   - **audit** — compare existing listing content with product truth 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.

Trust boundary

Read it. Change it. Keep the human in charge.

The skill requires read-only discovery by default, keeps live store changes behind explicit approval, and forbids invented metrics. It can make the work more legible; it cannot make an uncertain market certain.