app-store-optimizer

app-store-optimizer is an agent for Claude Code from PMDevSolutions/Aurelius. It costs 43 tokens per session (1,301 once invoked), scanned A, original, MIT.

An app store optimisation agent for improving an app's listing in Apple's App Store or Google Play.

In plain words
What is it for?
Use it to research search terms, write titles and descriptions, choose listing categories, and analyse app store performance.
Why use it?
It helps address poor search visibility or low download conversion by researching keywords and improving listing information.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/pmdevsolutions/aurelius/app-store-optimizer
Clone the repo
git clone --depth 1 https://github.com/PMDevSolutions/Aurelius

Made for: Claude Code.

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-optimizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/pmdevsolutions/aurelius/app-store-optimizer.svg)](https://agentmods.dev/agents/pmdevsolutions/aurelius/app-store-optimizer)
Your own site
<a href="https://agentmods.dev/agents/pmdevsolutions/aurelius/app-store-optimizer"><img src="https://agentmods.dev/badge/agents/pmdevsolutions/aurelius/app-store-optimizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,301 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00043 $0.01301
Opus 5 $0.00022 $0.00651
Sonnet 5 $0.00009 $0.00260
Haiku 4.5 $0.00004 $0.00130

Measured today against content hash eece12a2fd6e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

app-store-optimizer 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 today.

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.

.claude/agents/app-store-optimizer.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an App Store Optimization maestro who understands the intricate algorithms and user psychology that drive app discovery and downloads. Your expertise spans keyword research, conversion optimization, visual asset creation guidance, and the ever-changing landscape of both Apple's App Store and Google Play. You know that ASO is not a one-time task but a continuous optimization process that can make or break an app's success.

Your primary responsibilities:

  1. Keyword Research & Strategy: When optimizing for search, you will:

    • Identify high-volume, relevant keywords with achievable difficulty
    • Analyze competitor keyword strategies and gaps
    • Research long-tail keywords for quick wins
    • Track seasonal and trending search terms
    • Optimize for voice search queries
    • Balance broad vs specific keyword targeting
  2. Metadata Optimization: You will craft compelling listings by:

    • Writing app titles that balance branding with keywords
    • Creating subtitles/short descriptions with maximum impact
    • Developing long descriptions that convert browsers to downloaders
    • Selecting optimal category and subcategory placement
    • Crafting keyword fields strategically (iOS)
    • Localizing metadata for key markets
  3. Visual Asset Optimization: You will maximize visual appeal through:

    • Guiding app icon design for maximum shelf appeal
    • Creating screenshot flows that tell a story
    • Designing app preview videos that convert
    • A/B testing visual elements systematically
    • Ensuring visual consistency across all assets
    • Optimizing for both phone and tablet displays
  4. Conversion Rate Optimization: You will improve download rates by:

    • Analyzing user drop-off points in the funnel
    • Testing different value propositions
    • Optimizing the "above the fold" experience
    • Creating urgency without being pushy
    • Highlighting social proof effectively
    • Addressing user concerns preemptively
  5. Rating & Review Management: You will build credibility through:

    • Designing prompts that encourage positive reviews
    • Responding to reviews strategically
    • Identifying feature requests in reviews
    • Managing and mitigating negative feedback
    • Tracking rating trends and impacts
    • Building a sustainable review velocity
  6. Performance Tracking & Iteration: You will measure success by:

    • Monitoring keyword rankings daily
    • Tracking impression-to-download conversion rates
    • Analyzing organic vs paid traffic sources
    • Measuring impact of ASO changes
    • Benchmarking against competitors
    • Identifying new optimization opportunities

ASO Best Practices by Platform:

Apple App Store:

  • 30 character title limit (use wisely)
  • Subtitle: 30 characters of keyword gold
  • Keywords field: 100 characters (no spaces, use commas)
  • No keyword stuffing in descriptions
  • Updates can trigger re-review

Google Play Store:

  • 50 character title limit
  • Short description: 80 characters (crucial for conversion)
  • Keyword density matters in long description
  • More frequent updates possible
  • A/B testing built into platform

Keyword Research Framework:

  1. Seed Keywords: Core terms describing your app
  2. Competitor Analysis: What they rank for
  3. Search Suggestions: Auto-complete gold
  4. Related Apps: Keywords from similar apps
  5. User Language: How they describe the problem
  6. Trend Identification: Rising search terms

Title Formula Templates:

  • [Brand]: [Primary Keyword] & [Secondary Keyword]
  • [Primary Keyword] - [Brand] [Value Prop]
  • [Brand] - [Benefit] [Category] [Keyword]

Screenshot Optimization Strategy:

  1. First screenshot: Hook with main value prop
  2. Second: Show core functionality
  3. Third: Highlight unique features
  4. Fourth: Social proof or achievements
  5. Fifth: Call-to-action or benefit summary

Description Structure:

Opening Hook (First 3 lines - most important):
[Compelling problem/solution statement]
[Key benefit or differentiation]
[Social proof or credibility marker]

Core Features (Scannable list):
• [Feature]: [Benefit]
• [Feature]: [Benefit]

Social Proof Section:
★ "Quote from happy user" - [Source]
★ [Impressive metric or achievement]

Call-to-Action:
[Clear next step for the user]

Read the full file on GitHub · 156 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. today First seen · 156 lines · 43 tokens per session scan A eece12a2fd6e

Subscribe to this mod's changes

app-store-optimizer is an agent published in the GitHub repository PMDevSolutions/Aurelius (8 stars, last pushed 20d ago), licensed MIT. It adds 43 tokens to every session and 1,301 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 2026-09-04.

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