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 danielrosehill/Claude-Open-Router-Model-Research-Plugin --skill or-find-audio-modelsgit clone --depth 1 https://github.com/danielrosehill/Claude-Open-Router-Model-Research-PluginWrote 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/danielrosehill/claude-open-router-model-research-plugin/or-find-audio-models)<a href="https://agentmods.dev/skills/danielrosehill/claude-open-router-model-research-plugin/or-find-audio-models"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-open-router-model-research-plugin/or-find-audio-models/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/danielrosehill/claude-open-router-model-research-plugin/or-find-audio-models"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-open-router-model-research-plugin/or-find-audio-models.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 | $0.00067 | $0.00444 |
| Opus 5 | $0.00034 | $0.00222 |
| Sonnet 5 | $0.00013 | $0.00089 |
| Haiku 4.5 | $0.00007 | $0.00044 |
Grade A, and why
or-find-audio-models scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://openrouter.ai/api/v1/models -H "Accept: application/json" What it actually says
Find OpenRouter Audio-Input Models
Filter the OpenRouter catalog to models that accept audio input, then rank or summarize based on user criteria.
When to use
The user wants to discover models on OpenRouter that can process spoken/audio input — for transcription, voice understanding, audio QA, multimodal voice agents.
Workflow
- Fetch the catalog:
curl -s https://openrouter.ai/api/v1/models -H "Accept: application/json" - Filter
data[]wherearchitecture.input_modalitiesincludes"audio". - The audio-input model set on OpenRouter is small (often a handful of Gemini and GPT-4o variants). If the result set is empty, tell the user clearly and suggest alternatives:
- Use a dedicated STT API (Whisper, Deepgram, Gemini transcription) and pass text to an LLM
- Use a multimodal model that accepts text + image (a screenshot of a waveform or transcript) — usually wrong fit, mention only if relevant
- For each match, surface: supported audio formats (if listed in description), pricing (often charged per second or per token after transcription), and context length.
- If the user has a preference (cheapest, longest audio supported), rank accordingly.
Notes
- Audio pricing on OR varies — some models bill per audio token, others per audio second. Read the model description carefully and quote the relevant figure.
- Audio capability is a fast-moving area; the catalog is the source of truth — do not rely on memory for which models currently support audio.
Output
Markdown table or short list (since the set is small): ID, Context, Audio handling notes, Pricing notes, Caveats. If the set is empty, recommend a fallback workflow.
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 · 35 lines · 67 tokens per session scan A 894ca7ab5a7c
or-find-audio-models is a skill published in the GitHub repository danielrosehill/Claude-Open-Router-Model-Research-Plugin (2 stars, last pushed 4mo ago), licensed MIT. It adds 67 tokens to every session and 444 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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