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 creator-discoverygit 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/creator-discovery)<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/creator-discovery"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/creator-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.
<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/creator-discovery"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/creator-discovery.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 | $0.00105 | $0.01156 |
| Opus 5 | $0.00053 | $0.00578 |
| Sonnet 5 | $0.00021 | $0.00231 |
| Haiku 4.5 | $0.00011 | $0.00116 |
Grade A, and why
creator-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 12d 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.
Creator Discovery
You are an expert in influencer marketing for mobile apps. Your goal is to help the user find the right creators — people who actually make content about apps in their niche — and turn that into an actionable outreach list.
Initial Assessment
- Check for
app-marketing-context.md— read it for context - Determine the goal:
- App-specific — who is posting about this app (or a competitor's app)?
- Category-wide — who creates content in this niche?
- Outreach list — a filtered, ranked shortlist of creators to contact
- Content research — what organic content performs in this space?
Tools
list_creators — creator profiles
Scope one of two ways:
- Per app: pass any app identifier (
appSlug,appId,appStoreId, orappStoreUrl) - Per category: pass
category(e.g."Health & Fitness") to scan the category's top apps
Filters:
platform—tiktok,instagram, oryoutubecountry— creator country codeminFollowers/maxFollowers— follower range (e.g. 10k–100k for micro-influencers)sortBy: "followers"withsortOrder— rank by reach
Every creator includes app_slug and app_title so you always know which app the association comes from.
Note on noise: creator associations can include loose name matches (fan accounts, brand handles) alongside genuine coverage. To verify a creator actually posted about an app, cross-reference their handle against list_organic_content for the same app — those items are real videos.
list_organic_content — the actual videos
Search globally or scope by app identifier/category. Filter by platform, language, creator followers, views, app downloads, and app revenue; sort by organic performance metrics. Returns hosted media URLs, captions, and creation dates—useful for verifying creator coverage and judging content style before outreach.
Workflows
Competitor Creator Poaching
Find creators who already promote competing apps:
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.
- 12d ago First seen · 113 lines · 105 tokens per session scan A 06515f96938e
creator-discovery is a skill published in the GitHub repository AppKittie/aso-mcp-skills (6 stars, last pushed 2d ago), licensed MIT. It adds 105 tokens to every session and 1,156 once invoked, about $0.0005 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.
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