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 apify/awesome-skills --skill apify-app-store-intelligencegit clone --depth 1 https://github.com/apify/awesome-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/apify/awesome-skills/apify-app-store-intelligence)<a href="https://agentmods.dev/skills/apify/awesome-skills/apify-app-store-intelligence"><img src="https://agentmods.dev/badge/skills/apify/awesome-skills/apify-app-store-intelligence/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/apify/awesome-skills/apify-app-store-intelligence"><img src="https://agentmods.dev/badge/skills/apify/awesome-skills/apify-app-store-intelligence.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 | $0.00191 | $0.03485 |
| Opus 5.5 | $0.00076 | $0.01394 |
| Sonnet 5.5 | $0.00038 | $0.00697 |
| Haiku 4.5 | $0.00019 | $0.00348 |
Grade A, and why
apify-app-store-intelligence 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.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
App Store Intelligence (Apple App Store · Google Play)
Two different questions live under "get me app store data", and picking the wrong Actor for yours is the main way this task goes wrong:
- What does this app look like right now? — price, rating, ratings count, ratings histogram, version, developer, category, screenshots, release notes. This is metadata, it is one row per app, and it is cheap.
- What are users saying? — the review corpus. This is reviews, it is thousands of rows per app, and it costs roughly three orders of magnitude more per app.
Most Actors in this category do reviews. If the user asked "did our competitor drop their price", routing them to a reviews scraper burns their budget on data they did not ask for.
The second trap is the store: Apple and Google Play need different identifiers, different
Actors, and they do not carry the same fields (Google Play publishes a per-star histogram,
Apple does not publish one on the app page; Play metadata often has no version). Answer each
store from a run on that store — never infer one from the other.
Example prompts
Prompts this skill handles:
- "What's the current price and rating of App Store id 284882215?"
- "Resolve
com.spotify.clientto a full app record." - "Watch these six competitor apps daily and tell me when any of them changes price or ships a new version."
- "Pull the last 500 reviews of Duolingo on the US store."
- "Compare our app's rating in the US, UK and Japan storefronts."
- "Give me the 1–5 star breakdown for
com.calm.androidon Google Play." - "What are Android users complaining about in the last 30 days?"
Out of scope (the boundary):
- "How does my app rank for the keyword 'habit tracker'?" — that is keyword rank tracking,
which needs a rank tracker, not a metadata or review Actor. Hand off to
slothtechlabs/aso-keyword-rank-trackerorpetersutarik/aso-keyword-intel(references/actor-index.md); this skill does not run them. - "Which Shopify apps compete with mine?" — a different marketplace. This skill covers the Apple App Store and Google Play only.
What ships with it
2 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.
- 1mo ago First seen · 217 lines · 191 tokens per session scan A ff62e9b81e47
apify-app-store-intelligence is a skill published in the GitHub repository apify/awesome-skills (282 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 191 tokens to every session and 3,485 once invoked, about $0.0008 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 2026-09-22.
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