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 plahteenlahti/app-store-mcp --skill app-store-researchgit clone --depth 1 https://github.com/plahteenlahti/app-store-mcpWrote 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/plahteenlahti/app-store-mcp/app-store-research)<a href="https://agentmods.dev/skills/plahteenlahti/app-store-mcp/app-store-research"><img src="https://agentmods.dev/badge/skills/plahteenlahti/app-store-mcp/app-store-research/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/plahteenlahti/app-store-mcp/app-store-research"><img src="https://agentmods.dev/badge/skills/plahteenlahti/app-store-mcp/app-store-research.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 | $0.00049 | $0.00578 |
| Opus 5.5 | $0.00020 | $0.00231 |
| Sonnet 5.5 | $0.00010 | $0.00116 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
app-store-research 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 2mo 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 — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
App Store Research
Use the app_store_* MCP tools. Treat results as live public App Store data that can vary by country and change over time.
Narrowest path
- Fix the store country. Omit
countrywhen US results are acceptable; otherwise use one country consistently. This is complete when every country-sensitive call has an explicit or shared store. - Resolve each app once. Reuse a known numeric
idor bundleappIdinstead of searching again. This is complete when every target has an identifier or a confirmed no-result. - Select the narrowest calls and smallest useful result sets. This is complete when every call supplies evidence required by the request.
- Report only relevant fields. State the country for rankings, prices, ratings, and reviews; report errors or missing data without filling gaps. This is complete when facts from tools are distinguishable from conclusions.
Choose tools
- Discover apps: call
app_store_search. PreferidsOnly: truewhen only an ID is needed. Start withnum: 5or fewer. - Inspect one app: call
app_store_appwithidorappId. Setratings: truewhen metadata and the rating histogram are both needed; avoid a separate ratings call. - Read ratings only: call
app_store_ratingswith numericid. - Read reviews: call
app_store_reviews. Start at page 1; request more pages only when the user needs a larger sample. UsemostRecentormostHelpfulexplicitly when order matters. - Inspect privacy or releases: call
app_store_privacyorapp_store_version_historywith numericid. - Inspect monetization: call
app_store_in_app_purchaseswith numericid. Treat prices as localized display strings; Apple does not expose product identifiers or numeric amounts here. - Find related apps: call
app_store_similarwithidorappId. - Inspect a publisher: call
app_store_developerwith numericdevIdfrom app metadata. - Read charts: call
app_store_list. Keepnumsmall and setfullDetail: falseunless every result needs full metadata. - Complete a partial query: call
app_store_suggestonly when suggestions themselves help answer the request.
What ships with it
1 file 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.
- 2mo ago First seen · 33 lines · 49 tokens per session scan A f3f88ebeddbe
app-store-research is a skill published in the GitHub repository plahteenlahti/app-store-mcp (1 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 578 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 2026-08-31.
app-store-research compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| app-store-researchplahteenlahti/app-store-mcp | Skill | 1 | 2mo ago | MIT | A | 49 | Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |