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 lucholabs/applyra-aso-skill --skill applyra-asogit clone --depth 1 https://github.com/lucholabs/applyra-aso-skillWrote 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/lucholabs/applyra-aso-skill/applyra-aso)<a href="https://agentmods.dev/skills/lucholabs/applyra-aso-skill/applyra-aso"><img src="https://agentmods.dev/badge/skills/lucholabs/applyra-aso-skill/applyra-aso/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/lucholabs/applyra-aso-skill/applyra-aso"><img src="https://agentmods.dev/badge/skills/lucholabs/applyra-aso-skill/applyra-aso.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 | $0.00097 | $0.03969 |
| Opus 5 | $0.00048 | $0.01985 |
| Sonnet 5 | $0.00019 | $0.00794 |
| Haiku 4.5 | $0.00010 | $0.00397 |
Grade A, and why
applyra-aso 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 — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Applyra ASO
Run evidence-led App Store Optimization for Apple App Store and Google Play. Use the repository as product truth, Applyra as the ASO data source, and deterministic validation before proposing or writing metadata.
Portability and path resolution
This skill is portable across Codex, Claude Code, and other Agent Skills-compatible clients. Resolve skill-root as the directory containing this SKILL.md. Every relative reference, script, and asset path in this document is relative to skill-root; never assume the skill is installed under a specific home directory or repository path.
Respond and write reports in the user's language unless the repository establishes another language. Preserve store-facing copy in each target locale.
Core outcome
Produce an ASO system that is:
- True to the product — every claim maps to an implemented, available feature.
- Market-specific — every keyword decision is tied to store, country, and locale.
- Data-backed — Applyra metrics are quoted exactly and never invented.
- Conversion-aware — metadata and creatives answer the searcher's intent.
- Policy-safe — no competitor trademarks, false rankings, unsupported claims, or misleading assets.
- Reproducible — baseline, decisions, diffs, validation, and follow-up measurements are written to disk.
- Non-destructive by default — research first; Applyra mutations and store publication require explicit authorization.
- Data-minimized — raw private payloads stay local; public reports contain only normalized, redacted evidence.
Read before acting
- Read the root
AGENTS.mdand any nested instructions that apply to files you may change. - Read the relevant reference files for the requested phase:
- Applyra usage:
references/01-applyra-mcp.md - Product truth:
references/02-app-context.md - Keyword research:
references/03-keyword-research.md - Competitors:
references/04-competitors.md - Apple metadata:
references/05-apple-metadata.md - Google Play metadata:
references/06-google-play-metadata.md - Localization:
references/07-localization.md - Creatives and experiments:
references/08-creatives-conversion.md - Measurement:
references/09-measurement-experiments.md - Repository changes:
references/10-repository-integration.md - Compliance:
references/11-safety-compliance.md - Required outputs:
references/12-output-contract.md
- Applyra usage:
- Run
<skill-root>/scripts/check_setup.shwhen the Applyra connection, Node version, agent setup, or validator availability is uncertain.
What ships with it
26 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.
- agents/openai.yaml 680 B
- assets/app-context.template.yaml 1.1 KB
- assets/aso-report.template.md 1.1 KB
- assets/icon.png 8.1 KB
- assets/keyword-research.template.csv 250 B
- assets/logo.png 20 KB
- assets/metadata-manifest.template.json 628 B
- assets/readme-hero.png 1243 KB
- assets/store-surface-plan.template.json 679 B
- LICENSE.txt 1.0 KB
- references/01-applyra-mcp.md 7.6 KB
- references/02-app-context.md 3.6 KB
- references/03-keyword-research.md 5.6 KB
- references/04-competitors.md 3.1 KB
- references/05-apple-metadata.md 7.7 KB
- references/06-google-play-metadata.md 5.8 KB
- references/07-localization.md 2.8 KB
- references/08-creatives-conversion.md 5.8 KB
- references/09-measurement-experiments.md 5.2 KB
- references/10-repository-integration.md 3.4 KB
- references/11-safety-compliance.md 3.8 KB
- references/12-output-contract.md 4.3 KB
- scripts/check_setup.sh 4.0 KB runs code
- scripts/tests/test_validate_metadata.py 9.3 KB runs code
- scripts/validate_metadata.py 33 KB runs code
- VERSION 6 B
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 First seen · 392 lines · 97 tokens per session scan A 786b9ee618a5
applyra-aso is a skill published in the GitHub repository lucholabs/applyra-aso-skill (2 stars, last pushed 18d ago), licensed MIT. It adds 97 tokens to every session and 3,969 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
app-rejection-recovery
When the user's app or update was rejected by Apple App Review or Google Play Review and they need to diagnose why, fix it, and resubmit fast. Use when the user mentions "app rejected", "App Review rejection", "guideline violation", "Apple rejected my app", "Google Play rejected", "Play policy violation", "Resolution…
aso-router
Single entry point that routes any ASO, App Store, Google Play, app marketing, paid UA, monetization, retention, reviews, ratings, market-intel, or app-analytics question to the correct specialist skill in this library. Use FIRST whenever the user mentions an app, App Store, Play Store, keywords, ranking, downloads…
ab-test-store-listing
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see…
app-analytics
When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B testing, see ab-test-store-listing. For…
app-store-featured
When the user wants to get featured on the App Store or understand the editorial process. Also use when the user mentions "get featured", "App Store editorial", "App of the Day", "Today tab", "Apple featuring", or "how to get Apple to feature my app". For launch strategy, see app-launch. For ASO optimization, see…
apple-search-ads
When the user wants to set up, optimize, or scale Apple Search Ads (ASA) campaigns — including keyword bidding, match types, campaign structure, Creative Product Sets, CPP routing, and ROAS optimization. Use when the user mentions "Apple Search Ads", "ASA", "Search Ads", "Search tab ads", "Today tab ads", "CPT"…