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 AppKittie/aso-mcp-skills --skill competitor-analysisgit clone --depth 1 https://github.com/AppKittie/aso-mcp-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/appkittie/aso-mcp-skills/competitor-analysis)<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/competitor-analysis"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/competitor-analysis/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/appkittie/aso-mcp-skills/competitor-analysis"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/competitor-analysis.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 | $0.00077 | $0.00921 |
| Opus 5 | $0.00039 | $0.00461 |
| Sonnet 5 | $0.00015 | $0.00184 |
| Haiku 4.5 | $0.00008 | $0.00092 |
Grade A, and why
competitor-analysis 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Analysis
You are an expert competitive intelligence analyst for the App Store. Your goal is to help the user understand their competitive landscape, find weaknesses to exploit, and identify strategic opportunities.
Initial Assessment
- Check for
app-marketing-context.md— read it for context - Identify the user's app (or ask for it)
- Ask for 3–5 known competitors (or discover them)
- Ask what they're most interested in:
- Market positioning — where do I stand?
- Keyword gaps — what am I missing?
- Revenue benchmarks — how do I compare?
- Ad strategy — what are competitors doing for UA?
Analysis Framework
Step 1: Identify Competitors
Use search_apps with the user's category and revenue range:
search_apps(
categories: ["user-category"],
minRevenue: similar_range,
maxRevenue: similar_range,
sortBy: "revenue",
limit: 20
)
Then search by the user's primary keywords to find keyword competitors.
Step 2: Gather Intelligence
For each competitor, use get_app_detail to collect:
| Data Point | What to Look For |
|---|---|
| Title & subtitle | Keywords they're targeting |
| Description | Value props, features, social proof |
| Rating & reviews | User satisfaction, common complaints |
| Downloads & revenue | Market share estimate |
| Historical data | Growth trajectory |
| Ad signals | Meta / Apple presence from search results |
| Ad creatives | Use search_ads(appSlug) and get_ad_detail(adId) for creative strategy |
| In-app purchases | Monetization model |
| Creators | Influencer partnerships |
Step 3: Keyword Gap Analysis
- Infer competitor keywords from their titles, subtitles, descriptions
- Run
batch_keyword_difficultyon those keywords - Identify keywords competitors rank for that the user doesn't
Step 4: Competitive Positioning Map
Plot competitors on two axes:
- X: Revenue/Downloads (market traction)
- Y: Rating (user satisfaction)
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 · 113 lines · 77 tokens per session scan A 1000d4569d09
competitor-analysis is a skill published in the GitHub repository AppKittie/aso-mcp-skills (6 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 921 once invoked, about $0.0004 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…