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.
npx skills add seaworld008/Commonly-used-high-value-skills --skill app-store-optimizationgit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-skillsWrote 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/skills/seaworld008/commonly-used-high-value-skills/app-store-optimization)<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.
<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>- NVIDIA SkillSpector pass
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 | $0.00030 | $0.03701 |
| Opus 5 | $0.00015 | $0.01851 |
| Sonnet 5 | $0.00006 | $0.00740 |
| Haiku 4.5 | $0.00003 | $0.00370 |
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.
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.
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
- Metadata Optimization Workflow
- Competitor Analysis Workflow
- App Launch Workflow
- A/B Testing Workflow
- Before/After Examples
- Tools and References
Keyword Research Workflow
Discover and evaluate keywords that drive app store visibility.
Workflow: Conduct Keyword Research
- Define target audience and core app functions:
- Primary use case (what problem does the app solve)
- Target user demographics
- Competitive category
- Generate seed keywords from:
- App features and benefits
- User language (not developer terminology)
- App store autocomplete suggestions
- Expand keyword list using:
- Modifiers (free, best, simple)
- Actions (create, track, organize)
- Audiences (for students, for teams, for business)
- Evaluate each keyword:
- Search volume (estimated monthly searches)
- Competition (number and quality of ranking apps)
- Relevance (alignment with app function)
- Score and prioritize keywords:
- Primary: Title and keyword field (iOS)
- Secondary: Subtitle and short description
- Tertiary: Full description only
- Map keywords to metadata locations
- Document keyword strategy for tracking
- Validation: Keywords scored; placement mapped; no competitor brand names included; no plurals in iOS keyword field
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/aso-audit-template.md 4.8 KB
- expected_output.json 5.4 KB
- EXTENDED.md 1.1 KB
- HOW_TO_USE.md 10 KB
- README.md 15 KB
- references/aso-best-practices.md 12 KB
- references/keyword-research-guide.md 12 KB
- references/platform-requirements.md 9.4 KB
- sample_input.json 723 B
- scripts/ab_test_planner.py 22 KB runs code
- scripts/aso_scorer.py 19 KB runs code
- scripts/competitor_analyzer.py 21 KB runs code
- scripts/keyword_analyzer.py 13 KB runs code
- scripts/launch_checklist.py 28 KB runs code
- scripts/localization_helper.py 22 KB runs code
- scripts/metadata_optimizer.py 20 KB runs code
- scripts/review_analyzer.py 25 KB runs code
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.
- 4d ago Changed · -27 lines 89159a39fe6f
- 11d ago First seen · 515 lines · 30 tokens per session scan A b3f21e562511
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.
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