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.
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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.
[](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/app-store-optimizer)<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.
<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>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 | $0.00027 | $0.02551 |
| Opus 5.5 | $0.00011 | $0.01020 |
| Sonnet 5.5 | $0.00005 | $0.00510 |
| Haiku 4.5 | $0.00003 | $0.00255 |
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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- App Store Optimizer — 92% identical, 8 lines differ
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
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.
- 1mo ago First seen · 321 lines · 27 tokens per session scan A b245602501a3
App Store Optimizer is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (480 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 5.5. 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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