A planning guide for improving how an app appears in the Apple App Store and Google Play. App-store optimization (ASO) means making a listing easier to find and more convincing to people deciding whether to install it.

Use it to review store keywords, localized descriptions, screenshot order, and requests for user ratings.

A good app can still be missed if its keywords, language, screenshots, ratings prompts, or first impression are weak. It identifies listing changes that may improve discovery and installs.

plan-aso — Skill for Claude Code and Codex by kensaurus

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add kensaurus/cursor-kenji --skill plan-aso

Clone the repo

git clone --depth 1 https://github.com/kensaurus/cursor-kenji

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-aso/github.svg)](https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-aso)

Your own site

<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-aso"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-aso/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-aso"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-aso.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,343 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00066	$0.01343
Opus 5	$0.00033	$0.00672
Sonnet 5	$0.00013	$0.00269
Haiku 4.5	$0.00007	$0.00134

Measured 5d ago against content hash 55aff3eff9b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

plan-aso scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/plan-aso/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

plan-aso — Store listing growth plan

Degree of freedom: HIGH — audit the listing, emit a plan. Stay plan-only. No metadata, screenshot, or prompt edits until approved.

Role: Mobile growth / ASO specialist.

Task: Audit the listing that decides whether a visitor installs, emit plan-aso.md. Plan only — no metadata, screenshot, or prompt edits until approved.

ASO is two funnels: keywords decide who finds the app; screenshots + first impression decide who installs.

This skill vs neighbors

Skill	Owns
plan-aso (this)	Find + install conversion of the listing
`plan-mobile-readiness`	Submission mechanics, privacy manifest, demo account
`plan-privacy-compliance`	Honest privacy labels (don't ASO-lie about data)
`enhance-web-seo` / `plan-aeo-readiness`	Web / answer-engine discoverability
`audit-monetization-iap`	Whether IAP actually works
`design-frontend`	Asset production after the plan is approved

Do not fire for "will Play reject us / Guideline 2.5.2" → plan-mobile-readiness.

How to reason (every plan item)

Propose — keyword, locale, screenshot order, or ratings-prompt change
Risk — find vs install: who never sees the app, or who sees it and bounces
Keep-working — locales/assets that already convert
Phase — quick / medium / ongoing (do not execute)

Worked example

Propose: fill the unused 40 chars of the iOS keyword field; drop title-word repeats; put the benefit screenshot first. Risk: core use-case terms never indexed; first impression is a bare UI dump. Keep-working: JP long description already locale-native. Phase: quick — keywords + screenshot reorder. Find vs install: find (keywords) + install (shot 1).

Phase 0 — Gather the current listing [HIGH freedom]

Per platform × locale: name, subtitle (iOS) / short description (Android), iOS 100-char keyword field, long description, screenshots + captions, preview video, icon, category, ratings state. Note machine-translated or EN-only locales.

Read the full file on GitHub · 149 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

5d ago First seen · 149 lines · 66 tokens per session scan A 55aff3eff9b1

Subscribe to this mod's changes

plan-aso is a skill published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 11d ago), licensed MIT. It adds 66 tokens to every session and 1,343 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Marketing and SEO Mobile agent-skills ai-agent claude claude-skills cursor cursor-ai

flutter-pre-caching

Use when preloading fonts, asset/network images, Lottie/Rive animations, local JSON/config, warming initial API data, or optimizing Flutter Web startup.

evanca/flutter-ai-rules · 36 tokens

firebase-messaging

Use when setting up Firebase Cloud Messaging, managing permissions and tokens, handling background/foreground notification taps, or dispatching messages server-side (HTTP v1).

evanca/flutter-ai-rules · 35 tokens

bloc

Use when creating a Cubit or Bloc, modeling state with sealed classes or status enums, wiring BlocBuilder/BlocListener/BlocProvider, writing bloc tests, or choosing between Cubit and Bloc.

evanca/flutter-ai-rules · 42 tokens

firebase-database

Use when syncing real-time data, structuring JSON trees, reading/writing, creating listeners, enabling offline persistence, managing presence, sharding, or writing security rules.

evanca/flutter-ai-rules · 38 tokens

flutter-app-architecture

Use when scaffolding a project, refactoring into layers, creating view models/repositories, configuring dependency injection, or implementing unidirectional data flow (MVVM).