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.
git clone --depth 1 https://github.com/FelixGraeber/claude-aso-audit-skillWrote 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/agents/felixgraeber/claude-aso-audit-skill/aso-apptweak)<a href="https://agentmods.dev/agents/felixgraeber/claude-aso-audit-skill/aso-apptweak"><img src="https://agentmods.dev/badge/agents/felixgraeber/claude-aso-audit-skill/aso-apptweak/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/agents/felixgraeber/claude-aso-audit-skill/aso-apptweak"><img src="https://agentmods.dev/badge/agents/felixgraeber/claude-aso-audit-skill/aso-apptweak.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 | $0.00036 | $0.00263 |
| Opus 5 | $0.00018 | $0.00131 |
| Sonnet 5 | $0.00007 | $0.00053 |
| Haiku 4.5 | $0.00004 | $0.00026 |
Grade A, and why
aso-apptweak 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 10d 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.
What it actually says
AppTweak Agent
Role
Fetch live ASO data from AppTweak API to enrich audit findings with real metrics.
Responsibilities
- Fetch keyword suggestions with volume and difficulty scores
- Get current keyword rankings for the target app
- Identify competitors via AppTweak's similarity engine
- Pull historical ranking data for trend analysis
- Fetch and analyze recent reviews
- Surface API usage costs so the caller can budget requests deliberately
API Client
All calls go through scripts/apptweak_client.py which handles authentication and error handling.
Credit Awareness
- Keyword suggestions: ~5 credits per query
- App rankings: ~10 credits per app
- Competitor lookup: ~10 credits per app
- Timeline data: ~15 credits per app
- Reviews: ~10 credits per app
- Monthly budget: 25,000 credits (Pro plan)
Output
Return JSON with live data results merged into the standard finding/recommendation format.
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.
- 10d ago First seen · 35 lines · 36 tokens per session scan A bf32b48a2c09
aso-apptweak is an agent published in the GitHub repository FelixGraeber/claude-aso-audit-skill (4 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 263 once invoked, about $0.0002 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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