Borrowing it
Nothing to install: this file belongs to gaotiexinqu/OneResearchClaw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gaotiexinqu/OneResearchClaw/main/.cursor/skills/meeting-audio-grounding/SKILL.mdgit clone --depth 1 https://github.com/gaotiexinqu/OneResearchClawWrote 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/gaotiexinqu/oneresearchclaw/meeting-audio-grounding)<a href="https://agentmods.dev/skills/gaotiexinqu/oneresearchclaw/meeting-audio-grounding"><img src="https://agentmods.dev/badge/skills/gaotiexinqu/oneresearchclaw/meeting-audio-grounding/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/gaotiexinqu/oneresearchclaw/meeting-audio-grounding"><img src="https://agentmods.dev/badge/skills/gaotiexinqu/oneresearchclaw/meeting-audio-grounding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.01020 |
| Opus 5 | $0.00014 | $0.00510 |
| Sonnet 5 | $0.00006 | $0.00204 |
| Haiku 4.5 | $0.00003 | $0.00102 |
Grade A, and why
meeting-audio-grounding 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 13d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Audio Grounding
Convert a meeting audio file into structured meeting grounding outputs by:
- reusing the existing
audio_structuringskill to producemeeting_transcript.txt - reusing the existing
meeting-groundingskill to turn that transcript into meeting grounding outputs
This skill is for meeting audio inputs where the primary information comes from speech. It is intentionally transcript-first.
When to Use
Use this skill when:
- the input is a meeting recording or discussion audio file
- the main information is expected to come from spoken content
- you want to reuse the existing audio transcription and meeting grounding workflow
Do not use this skill when:
- the task is only to produce a transcript without meeting grounding
- the task is to write a polished final report directly from raw audio
- the input is not a meeting/discussion recording
Input
A single meeting audio file.
Typical examples:
.mp3.wav.m4a.webm.aac.ogg
All these formats are supported via WhisperX's ffmpeg backend.
Optional input:
transcription_language: language code such asenorzh
Output Bundle
For each input audio file, create one bundle directory:
data/grounded_notes/<ground_id>/
Inside that bundle, the expected outputs are always:
<bundle_dir>/
├─ extracted.md
├─ extracted_meta.json
├─ grounded.md
├─ audio/
│ └─ meeting_audio<original_ext>
└─ transcript/
└─ meeting_transcript.txt
If the meeting contains multiple independent topics that should be researched separately downstream, the bundle may also contain:
<bundle_dir>/
├─ topic_manifest.json
└─ child_outputs/
├─ topic_01/
│ └─ grounded.md
├─ topic_02/
│ └─ grounded.md
└─ ...
Important separation of responsibilities
scripts/run.shis responsible for:- preparing the bundle directory
- ensuring the input audio is present under
audio/ - calling the existing
audio_structuringskill - creating the bundle files:
audio/meeting_audio<original_ext>transcript/meeting_transcript.txtextracted.mdextracted_meta.json
- The agent is responsible for:
- reading the transcript bundle
- applying the existing
meeting-groundingskill - always writing the meeting-level:
grounded.md
- and, when appropriate, also writing:
topic_manifest.jsonchild_outputs/topic_xx/grounded.md
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 149 lines · 28 tokens per session scan A 5197e217c74e
meeting-audio-grounding is a skill published in the GitHub repository gaotiexinqu/OneResearchClaw (446 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 1,020 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 2026-08-30.
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