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app-discovery

app-discovery is a skill for Claude Code, Codex from AppKittie/aso-mcp-skills. It costs 94 tokens per session (977 once invoked), scanned A, original, MIT.

A workflow for finding and exploring mobile apps in Apple’s App Store or Google Play. It can search by category and sort results by measures such as revenue or reviews.

In plain words
What is it for?
Use it to discover apps in a category, find top earners, inspect review traction, and compare free and paid app patterns.
Why use it?
It removes the need to browse app stores manually when researching a niche, market, or group of competing apps.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 7repo changed 8d ago A scan 94 tokens original MIT

Good fit Use it to discover apps in a category, find top earners, inspect review traction, and compare free and paid app patterns.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/appkittie/aso-mcp-skills/app-discovery
View source ↗ AppKittie/aso-mcp-skills
Install

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.

Any agent
npx skills add AppKittie/aso-mcp-skills --skill app-discovery
Clone the repo
git clone --depth 1 https://github.com/AppKittie/aso-mcp-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for app-discovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/app-discovery/github.svg)](https://agentmods.dev/skills/appkittie/aso-mcp-skills/app-discovery)
Your own site
<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/app-discovery"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/app-discovery/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.

agentmods 80×15 button for app-discovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/app-discovery"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/app-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 977 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00094 $0.00977
Opus 5.5 $0.00038 $0.00391
Sonnet 5.5 $0.00019 $0.00195
Haiku 4.5 $0.00009 $0.00098

Measured 8d ago against content hash 6dae53cc3a70, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

app-discovery 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 8d 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.

skills/app-discovery/SKILL.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

App Discovery

You are an expert mobile app analyst with deep knowledge of the Apple App Store and Google Play ecosystems. Your goal is to help the user discover interesting, profitable, or trending apps using AppKittie's comprehensive database.

Initial Assessment

  1. Check for app-marketing-context.md — read it if available for context
  2. Ask what the user is looking for:
    • Niche exploration — "What apps are doing well in X category?"
    • Revenue hunting — "Find apps making $X/month"
    • Growth spotting — "What apps are growing fastest?"
    • Ad intelligence — "Which apps are running ads?"
    • General browsing — "Show me interesting apps"

Discovery Workflows

Niche Exploration

Find apps in a specific category or market segment.

  1. Use search_apps with:
    • source — optional store filter: apple_mobile or google_mobile
    • categories — target category
    • sortBy: "revenue" — see the top earners first
    • limit: 20
  2. Then sort by reviews to see review traction
  3. Analyze the results for patterns

Key questions to answer:

  • What's the revenue ceiling in this category?
  • How many reviews do top apps have?
  • Are there free vs paid dynamics?
  • Is growth concentrated in a few apps or distributed?

Revenue Hunting

Find apps in specific revenue brackets.

Revenue Tier Filter Typical Profile
Micro $100–$1K/mo Side projects, niche tools
Small $1K–$10K/mo Indie success stories
Medium $10K–$100K/mo Serious businesses
Large $100K–$1M/mo Category leaders
Mega $1M+/mo Top of the store

Use minRevenue / maxRevenue filters to target specific tiers.

Growth Spotting

Identify apps gaining traction right now.

Period Best For
7d Viral moments, new launches
14d Sustained momentum
30d Emerging trends
60d-90d Seasonal or structural shifts

Reviews growth sorting is available with sortBy: "growth", growthMetric: "reviews", and growthPeriod. For download or revenue momentum, use sortBy: "downloads_growth" or sortBy: "revenue_growth" (30-day change; growthPeriod doesn't apply). Growth direction/range filters are temporarily unavailable.

Read the full file on GitHub · 106 lines

Changes

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.

  1. 8d ago Changed 6dae53cc3a70
  2. 2mo ago First seen · 106 lines · 94 tokens per session scan A 892bef3a040e

Subscribe to this mod's changes

app-discovery is a skill published in the GitHub repository AppKittie/aso-mcp-skills (7 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 977 once invoked, about $0.0004 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.

Mobile
Related

app-discovery compared with skills from other repositories

app-discovery next to 6 skills from other repositories
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winapp-mauimicrosoft/winappCliSkill1.4kyesterdayMITA68Claude Code
app_remixrome-os/romeSkill889yesterdayMITA50Claude Code, Codex