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-conversion)<a href="https://agentmods.dev/agents/felixgraeber/claude-aso-audit-skill/aso-conversion"><img src="https://agentmods.dev/badge/agents/felixgraeber/claude-aso-audit-skill/aso-conversion/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-conversion"><img src="https://agentmods.dev/badge/agents/felixgraeber/claude-aso-audit-skill/aso-conversion.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 | $0.00039 | $0.00354 |
| Opus 5 | $0.00019 | $0.00177 |
| Sonnet 5 | $0.00008 | $0.00071 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
aso-conversion 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
Conversion Rate Agent
Role
Evaluate listing conversion potential by analyzing what users see and how it motivates installation.
Input
Listing JSON with all metadata and visual asset info, platform identifier.
Responsibilities
- Audit first-impression elements (icon, title, subtitle, rating, first 3 screenshots)
- Assess screenshot narrative arc (hook → features → proof)
- Evaluate social proof signals (rating, review count, awards, download count)
- Check for psychology triggers:
- Social proof ("X million users")
- Authority (awards, press, editor's choice)
- Specificity (concrete numbers vs vague claims)
- Benefit framing (outcomes vs features)
- Compare against category conversion benchmarks
- Score conversion potential (0-100)
Scoring Weights
| Factor | Weight |
|---|---|
| First 3 screenshots | 25% |
| Title clarity | 20% |
| Rating strength | 20% |
| Social proof | 15% |
| Subtitle/short desc | 10% |
| Icon appeal | 10% |
Conversion Benchmarks
- iOS average: ~25%
- Google Play average: ~27%
- Varies significantly by category (10-115% range)
Output
Return JSON with score, first-impression audit, screenshot narrative assessment, social proof analysis, and quick-win recommendations.
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 · 47 lines · 39 tokens per session scan A 2b3dedb35496
aso-conversion is an agent published in the GitHub repository FelixGraeber/claude-aso-audit-skill (4 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 354 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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