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 Gingiris-1031/gingiris-skills --skill aso-playbookgit clone --depth 1 https://github.com/Gingiris-1031/gingiris-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/gingiris-1031/gingiris-skills/aso-playbook)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/aso-playbook"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/aso-playbook/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/gingiris-1031/gingiris-skills/aso-playbook"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/aso-playbook.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 | $0.00048 | $0.00967 |
| Opus 5.5 | $0.00019 | $0.00387 |
| Sonnet 5.5 | $0.00010 | $0.00193 |
| Haiku 4.5 | $0.00005 | $0.00097 |
Grade A, and why
aso-playbook 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 11d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
📦 Install
clawhub install aso-playbook
What you get after installing:
- Keyword research methodology for finding low-competition, high-intent terms
- Screenshot hypothesis and message-hierarchy framework
- A/B testing and evidence-capture framework for iOS and Android
App Store Optimization Basics — Keywords, Screenshots & Ratings
The fundamentals of ASO for developers who'd rather build than market — but need downloads.
- Keyword research: Finding low-competition, high-intent keywords for your category
- Screenshot optimization: Turn user intent into testable screenshot hypotheses
- Rating strategy: How to ask for reviews without annoying users
- Localization basics: Which markets to target first and how to test
- A/B testing: What to test, how long to run, and interpreting results
Minimum viable ASO workflow
- Export the last 28 days by country and traffic source: impressions, product-page views, first-time downloads, conversion rate, proceeds, D1/D7/D30 retention.
- Build a keyword sheet with relevance, current rank, search popularity, competition, destination locale and target page.
- Change one variable family at a time: metadata, icon, first three screenshots, preview video, rating prompt or localization.
- Record the exact before/after version, release date, storefront and external UA activity.
- Keep a test only when conversion improves without a material decline in retained users, rating quality or revenue.
Evidence gate
Do not claim an ASO win from downloads alone. A valid case needs, at minimum:
- keyword rank or search-impression change;
- impression → product-page-view rate;
- product-page-view → first-time-download rate;
- D7 or D30 retained-user outcome;
- dates, storefronts, app version and paid-campaign overlap.
No controlled Gingiris App Store before/after dataset is bundled with this skill yet. The workflow is executable; any uplift claim must come from the user's own App Store Connect or Play Console export.
What ships with it
5 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.
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.
- 11d ago Changed · +14 lines 0979204db96e
- 1mo ago First seen · 77 lines · 48 tokens per session scan A 2f431bd6ddee
aso-playbook is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (87 stars, last pushed 11d ago), licensed MIT. It adds 48 tokens to every session and 967 once invoked, about $0.0002 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.
Other skills, from other repositories
aso-atlas
App Store Optimization with ASO Atlas. Use for App Store and Google Play keyword research (popularity, difficulty, who ranks), tracking an app's keyword rankings per storefront, competitor keyword gaps, metadata (title, subtitle, keyword field) drafts, and questions like "how is my app doing" answered from App Store…
aso
Route or run comprehensive App Store Optimization work for iOS and Android. Use for full listing audits, multi-area ASO requests, or when the user does not name a more specific ASO task. Covers keyword research, metadata, visuals, reviews, competitors, localization, testing, technical health, compliance, conversion…
aso-apptweak
Live ASO data via AppTweak REST API. Keyword suggestions with volume/difficulty, app rankings, competitor analysis, review sentiment, and historical data. Requires AppTweak API key. Triggers on: "apptweak", "live data", "keyword volume".
aso-asc
Apple App Store Connect API integration. Fetch iOS app metadata, reviews, ratings, and version info directly from App Store Connect. Requires API key. Triggers on: "app store connect", "asc".
aso-creative
Improve app-store screenshots, preview video, icon presentation, conversion, and store experiments for Apple App Store and Google Play.
aso-listing
Research and improve app-store keywords, metadata, localization, and seasonal listing changes for Apple App Store and Google Play.