app-store-optimization

app-store-optimization is a skill for Claude Code, Codex from sickn33/agentic-awesome-skills. It costs 32 tokens per session (3,722 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 researching search terms, competitors, reviews, and listing text to help people find and choose an app.

In plain words
What is it for?
Use it to research keywords and competitors, analyze reviews and trends, and improve titles, descriptions, promotional text, keywords, and store categories.
Why use it?
It helps identify why an app may be hard to discover or unconvincing in a store listing.

Skill for Claude CodeCodex

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

Part of the agentic-awesome-skills plugin — 196 skills shipped together

Good fit Use it to research keywords and competitors, analyze reviews and trends, and improve titles, descriptions, promotional text, keywords, and store categories.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sickn33/agentic-awesome-skills/app-store-optimization
About the project

AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.

sickn33/agentic-awesome-skills · 46,133 stars · on GitHub · sickn33.github.io

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 sickn33/agentic-awesome-skills --skill app-store-optimization
Clone the repo
git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills

Made for: Claude Code, Codex.

Or install agentic-awesome-skills, the plugin that ships this one along with the rest of its 196 skills.

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/sickn33/agentic-awesome-skills/app-store-optimization/github.svg)](https://agentmods.dev/skills/sickn33/agentic-awesome-skills/app-store-optimization)
Your own site
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/app-store-optimization"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-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/sickn33/agentic-awesome-skills/app-store-optimization"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/app-store-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,722 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
  • Socket pass 31 Jul 2026
  • Snyk pass 31 Jul 2026
  • 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 $0.00032 $0.03722
Opus 5 $0.00016 $0.01861
Sonnet 5 $0.00006 $0.00744
Haiku 4.5 $0.00003 $0.00372

Measured 3d ago against content hash 2804d2cca1d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, 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 3d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (ab_test_planner.py, aso_scorer.py, 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.

Origin

Copies of this mod

8 near-identical copies found in the catalogue:

plugins/agentic-awesome-skills-claude/skills/app-store-optimization/SKILL.md · 417 lines

How it starts

The opening of the file, as written. The whole thing — 417 lines — stays where its author put it; the contents beside it link to each section on GitHub.

App Store Optimization (ASO) Skill

This comprehensive skill provides complete ASO capabilities for successfully launching and optimizing mobile applications on the Apple App Store and Google Play Store.

Capabilities

Research & Analysis

  • Keyword Research: Analyze keyword volume, competition, and relevance for app discovery
  • Competitor Analysis: Deep-dive into top-performing apps in your category
  • Market Trend Analysis: Identify emerging trends and opportunities in your app category
  • Review Sentiment Analysis: Extract insights from user reviews to identify strengths and issues
  • Category Analysis: Evaluate optimal category and subcategory placement strategies

Metadata Optimization

  • Title Optimization: Create compelling titles with optimal keyword placement (platform-specific character limits)
  • Description Optimization: Craft both short and full descriptions that convert and rank
  • Subtitle/Promotional Text: Optimize Apple-specific subtitle (30 chars) and promotional text (170 chars)
  • Keyword Field: Maximize Apple's 100-character keyword field with strategic selection
  • Category Selection: Data-driven recommendations for primary and secondary categories
  • Icon Best Practices: Guidelines for designing high-converting app icons
  • Screenshot Optimization: Strategies for creating screenshots that drive installs
  • Preview Video: Best practices for app preview videos
  • Localization: Multi-language optimization strategies for global reach

Conversion Optimization

  • A/B Testing Framework: Plan and track metadata experiments for continuous improvement
  • Visual Asset Testing: Test icons, screenshots, and videos for maximum conversion
  • Store Listing Optimization: Comprehensive page optimization for impression-to-install conversion
  • Call-to-Action: Optimize CTAs in descriptions and promotional materials

Rating & Review Management

  • Review Monitoring: Track and analyze user reviews for actionable insights
  • Response Strategies: Templates and best practices for responding to reviews
  • Rating Improvement: Tactical approaches to improve app ratings organically
  • Issue Identification: Surface common problems and feature requests from reviews

Read the full file on GitHub · 417 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. 3d ago First seen · 417 lines · 32 tokens per session scan A 2804d2cca1d0

Subscribe to this mod's changes

app-store-optimization is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,133 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 3,722 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 2026-09-05.