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 robertguss/claude-code-toolkit --skill app-store-opportunity-researchgit clone --depth 1 https://github.com/robertguss/claude-code-toolkitWrote 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/robertguss/claude-code-toolkit/app-store-opportunity-research)<a href="https://agentmods.dev/skills/robertguss/claude-code-toolkit/app-store-opportunity-research"><img src="https://agentmods.dev/badge/skills/robertguss/claude-code-toolkit/app-store-opportunity-research.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00130 | $0.05117 |
| Opus 5 | $0.00065 | $0.02559 |
| Sonnet 5 | $0.00026 | $0.01023 |
| Haiku 4.5 | $0.00013 | $0.00512 |
Grade A, and why
app-store-opportunity-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 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.
How it starts
The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prerequisites
- Browser tools for App Store browsing and research
- Web search for Reddit, Google Trends, and indie revenue research
- No API keys required — all research is done through browser and web search
Pipeline Overview
1. Define Category & Goals
2. App Store Charts Research
3. Community & Demand Research
4. Competitor Deep-Dive
5. Revenue Deep-Dive
6. Gap Analysis
7. Score & Rank
8. Top 3 Report
9. Quick Validation (optional)
10. MVP PRD
Step 1: Define the Category & Goals
Ask the user what space they want to explore. Help them narrow down:
- Too broad: "Health apps" (thousands of competitors)
- Good: "Sleep + anxiety apps for consumers" (specific intersection)
- Good: "Habit tracking for fitness beginners" (audience + niche)
- Good: "AI-powered journaling apps" (tech angle + category)
Key questions to ask:
- What category or problem space interests you?
- Consumer or B2B? (Consumer is easier to validate quickly)
- Any budget constraints? (No-AI = cheaper to build, AI = higher ceiling)
- Target revenue? ($1K/mo side project vs $10K/mo business vs $50K+/mo full-time replacement)
- What's your timeline? (2-4 week MVP vs 2-3 month polished launch)
- Do you have domain expertise or personal pain in this area? (Strongest apps come from scratching your own itch)
Step 2: App Store Charts Research
Browse the iOS App Store charts to map the competitive landscape.
Chart URLs
Navigate to: https://apps.apple.com/us/charts/iphone/{category-slug}/{category-id}
Apps:
| Category | Path |
|---|---|
| Books | /books-apps/6018 |
| Business | /business-apps/6000 |
| Education | /education-apps/6017 |
| Entertainment | /entertainment-apps/6016 |
| Finance | /finance-apps/6015 |
| Food & Drink | /food-drink-apps/6023 |
| Graphics & Design | /graphics-design-apps/6027 |
| Health & Fitness | /health-fitness-apps/6013 |
| Lifestyle | /lifestyle-apps/6012 |
| Medical | /medical-apps/6020 |
| Music | /music-apps/6011 |
| Navigation | /navigation-apps/6010 |
| News | /news-apps/6009 |
| Photo & Video | /photo-video-apps/6008 |
| Productivity | /productivity-apps/6007 |
| Reference | /reference-apps/6006 |
| Shopping | /shopping-apps/6024 |
| Social Networking | /social-networking-apps/6005 |
| Sports | /sports-apps/6004 |
| Travel | /travel-apps/6003 |
| Utilities | /utilities-apps/6002 |
| Weather | /weather-apps/6001 |
What ships with it
6 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.
- 8d ago First seen · 488 lines · 130 tokens per session scan A f79e959f1b0c
app-store-opportunity-research is a skill published in the GitHub repository robertguss/claude-code-toolkit (113 stars, last pushed 1mo ago), licensed MIT. It adds 130 tokens to every session and 5,117 once invoked, about $0.0006 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 2026-08-30.
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