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 | $0.00772 |
| Opus 5 | $0.00024 | $0.00386 |
| Sonnet 5 | $0.00010 | $0.00154 |
| Haiku 4.5 | $0.00005 | $0.00077 |
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 10d 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 — 77 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.
- 10d 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 (79 stars, last pushed 5d ago), licensed MIT. It adds 48 tokens to every session and 772 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.
Other skills, from other repositories
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-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-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-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.
aso-release
Check app-store technical readiness, policy compliance, launch preparation, indexing factors, product-page requirements, and release-day monitoring.