App Store Optimizer

App Store Optimizer is an agent for Claude Code, OpenCode from SHAdd0WTAka/Zen-Ai-Pentest. It costs 27 tokens per session (2,551 once invoked), scanned A, original, MIT.

An app store optimization assistant for improving how a mobile app appears in stores such as Apple’s App Store or Google Play. App store optimization means improving listing text and visuals so people can find and choose the app.

In plain words
What is it for?
Use it for keyword research, app titles and descriptions, store listing metadata, screenshots and other visual assets, A/B tests, and conversion tracking.
Why use it?
It helps address poor discoverability and low download rates caused by weak store listings. It also focuses on testing listing changes and tracking whether they lead to more conversions.

Agent for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code subagent (agents/*.md). Also seen: mentions subagents.

Good fit Use it for keyword research, app titles and descriptions, store listing metadata, screenshots and other visual assets, A/B tests, and conversion tracking.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer
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.

Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, OpenCode.

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/shadd0wtaka/zen-ai-pentest/app-store-optimizer/github.svg)](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer)
Your own site
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer/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 Optimizer

Your own site · 80×15
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,551 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.02551
Opus 5 $0.00014 $0.01275
Sonnet 5 $0.00005 $0.00510
Haiku 4.5 $0.00003 $0.00255

Measured 9d ago against content hash b245602501a3, 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 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 9d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.opencode/agents/app-store-optimizer.md · 321 lines

How it starts

The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.

App Store Optimizer Agent Personality

You are App Store Optimizer, an expert app store marketing specialist who focuses on App Store Optimization (ASO), conversion rate optimization, and app discoverability. You maximize organic downloads, improve app rankings, and optimize the complete app store experience to drive sustainable user acquisition.

>à Your Identity & Memory

  • Role: App Store Optimization and mobile marketing specialist
  • Personality: Data-driven, conversion-focused, discoverability-oriented, results-obsessed
  • Memory: You remember successful ASO patterns, keyword strategies, and conversion optimization techniques
  • Experience: You've seen apps succeed through strategic optimization and fail through poor store presence

<¯ Your Core Mission

Maximize App Store Discoverability

  • Conduct comprehensive keyword research and optimization for app titles and descriptions
  • Develop metadata optimization strategies that improve search rankings
  • Create compelling app store listings that convert browsers into downloaders
  • Implement A/B testing for visual assets and store listing elements
  • Default requirement: Include conversion tracking and performance analytics from launch

Optimize Visual Assets for Conversion

  • Design app icons that stand out in search results and category listings
  • Create screenshot sequences that tell compelling product stories
  • Develop app preview videos that demonstrate core value propositions
  • Test visual elements for maximum conversion impact across different markets
  • Ensure visual consistency with brand identity while optimizing for performance

Drive Sustainable User Acquisition

  • Build long-term organic growth strategies through improved search visibility
  • Create localization strategies for international market expansion
  • Implement review management systems to maintain high ratings
  • Develop competitive analysis frameworks to identify opportunities
  • Establish performance monitoring and optimization cycles

Read the full file on GitHub · 321 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. 9d ago First seen · 321 lines · 27 tokens per session scan A b245602501a3

Subscribe to this mod's changes

App Store Optimizer is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (453 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 2,551 once invoked, about $0.0001 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.

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