app-store-optimization

app-store-optimization is a skill for Claude Code, Codex from seaworld008/Commonly-used-high-value-skills. It costs 30 tokens per session (3,701 once invoked), scanned A, original, MIT.

A toolkit for improving how a mobile app appears and performs in the Apple App Store and Google Play Store. App Store Optimization means improving store text and visuals so relevant users can find the app.

In plain words
What is it for?
Use it to research keywords, improve store metadata and screenshots, study competing apps, prepare a launch, plan experiments, and track results.
Why use it?
It gives a structured way to research search terms and competitors instead of guessing which title, description, or screenshots will attract users.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to research keywords, improve store metadata and screenshots, study competing apps, prepare a launch, plan experiments, and track results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/seaworld008/commonly-used-high-value-skills/app-store-optimization
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 seaworld008/Commonly-used-high-value-skills --skill app-store-optimization
Clone the repo
git clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-skills

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.

agentmods badge for app-store-optimization

README.md
[![agentmods](https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization/github.svg)](https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization)
Your own site
<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization/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.

agentmods 80×15 button for app-store-optimization

Your own site · 80×15
<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,701 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.03701
Opus 5 $0.00015 $0.01851
Sonnet 5 $0.00006 $0.00740
Haiku 4.5 $0.00003 $0.00370

Measured 4d ago against content hash 89159a39fe6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

app-store-optimization 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 4d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/ab_test_planner.py, scripts/aso_scorer.py, scripts/competitor_analyzer.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

openclaw-skills/app-store-optimization/SKILL.md · 488 lines

How it starts

The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.

App Store Optimization (ASO)

ASO tools for researching keywords, optimizing metadata, analyzing competitors, and improving app store visibility on Apple App Store and Google Play Store.

When to Use

Use this skill when the user wants to:

  • improve App Store or Google Play discoverability
  • research keywords and metadata for a mobile app
  • analyze competitors in app stores
  • prepare a launch or plan ASO experiments
  • optimize screenshots, title, subtitle, or store copy

Usage

Recommended flow:

understand app and audience
-> research keywords and competitors
-> optimize metadata and visuals
-> plan launch or A/B test
-> track learnings and iterate

Table of Contents


Keyword Research Workflow

Discover and evaluate keywords that drive app store visibility.

Workflow: Conduct Keyword Research

  1. Define target audience and core app functions:
    • Primary use case (what problem does the app solve)
    • Target user demographics
    • Competitive category
  2. Generate seed keywords from:
    • App features and benefits
    • User language (not developer terminology)
    • App store autocomplete suggestions
  3. Expand keyword list using:
    • Modifiers (free, best, simple)
    • Actions (create, track, organize)
    • Audiences (for students, for teams, for business)
  4. Evaluate each keyword:
    • Search volume (estimated monthly searches)
    • Competition (number and quality of ranking apps)
    • Relevance (alignment with app function)
  5. Score and prioritize keywords:
    • Primary: Title and keyword field (iOS)
    • Secondary: Subtitle and short description
    • Tertiary: Full description only
  6. Map keywords to metadata locations
  7. Document keyword strategy for tracking
  8. Validation: Keywords scored; placement mapped; no competitor brand names included; no plurals in iOS keyword field

Read the full file on GitHub · 488 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.

  1. 4d ago Changed · -27 lines 89159a39fe6f
  2. 11d ago First seen · 515 lines · 30 tokens per session scan A b3f21e562511

Subscribe to this mod's changes

app-store-optimization is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 4d ago), licensed MIT. It adds 30 tokens to every session and 3,701 once invoked, about $0.0002 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 2026-08-30.