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-reviews)<a href="https://agentmods.dev/agents/felixgraeber/claude-aso-audit-skill/aso-reviews"><img src="https://agentmods.dev/badge/agents/felixgraeber/claude-aso-audit-skill/aso-reviews/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-reviews"><img src="https://agentmods.dev/badge/agents/felixgraeber/claude-aso-audit-skill/aso-reviews.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 | $0.00028 | $0.00425 |
| Opus 5 | $0.00014 | $0.00212 |
| Sonnet 5 | $0.00006 | $0.00085 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
aso-reviews 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.
What it actually says
Review Analysis Agent
Role
Analyze app reviews and ratings for health signals, sentiment trends, and keyword opportunities.
Input
Listing JSON with rating data, reviews (if available), platform identifier.
Responsibilities
- Analyze rating: average, count, distribution
- Run
scripts/review_analyzer.pyif review text is available - Classify sentiment: positive/neutral/negative percentages
- Extract theme clusters: performance, UI, features, pricing, bugs, support
- Identify keyword opportunities from review language (Android: reviews are indexed!)
- Assess developer response rate and quality
- Score overall review health (0-100)
Scoring Weights
| Factor | Weight | Thresholds |
|---|---|---|
| Average rating | 30% | <3.5=Critical, 3.5-4.0=Poor, 4.0-4.5=Good, 4.5+=Excellent |
| Rating volume | 20% | <100=Low, 100-1000=Moderate, >1000=Strong |
| Sentiment ratio | 20% | >70% positive=Good, 50-70%=Fair, <50%=Poor |
| Rating trend | 15% | Improving=bonus, stable=neutral, declining=penalty |
| Response rate | 15% | >80%=Excellent, 50-80%=Good, <50%=Needs work |
Platform-Specific Notes
- iOS: review text NOT indexed for search. Focus on rating signals.
- Android: review text IS indexed. Keywords in reviews boost rankings.
Output
Return JSON with score, findings (rating health, sentiment breakdown, key themes), and recommendations (response priorities, keyword opportunities from reviews).
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 · 42 lines · 28 tokens per session scan A d2c73f626766
aso-reviews is an agent published in the GitHub repository FelixGraeber/claude-aso-audit-skill (4 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 425 once invoked, about $0.0001 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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