Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/cyberbird2048/gbrainmcp-cleannpx agentmods add skills/cyberbird2048/gbrainmcp-clean/voice-note-ingestWrote 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/cyberbird2048/gbrainmcp-clean/voice-note-ingest)<a href="https://agentmods.dev/skills/cyberbird2048/gbrainmcp-clean/voice-note-ingest"><img src="https://agentmods.dev/badge/skills/cyberbird2048/gbrainmcp-clean/voice-note-ingest/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/cyberbird2048/gbrainmcp-clean/voice-note-ingest"><img src="https://agentmods.dev/badge/skills/cyberbird2048/gbrainmcp-clean/voice-note-ingest.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 | $0.00056 | $0.01590 |
| Opus 5 | $0.00028 | $0.00795 |
| Sonnet 5 | $0.00011 | $0.00318 |
| Haiku 4.5 | $0.00006 | $0.00159 |
Grade A, and why
voice-note-ingest 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.
This is a copy
100% identical to voice-note-ingest — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
voice-note-ingest — Exact-Phrasing Voice Capture
Convention: see conventions/quality.md for citation rules, back-link enforcement, and exact-phrasing requirements.
Convention: see _brain-filing-rules.md for the filing decision protocol.
Iron Law
The user's exact words are the insight. Never paraphrase. Never clean up. The vivid, unpolished, stream-of-consciousness phrasing captures something that cleaned-up prose does not. Preserve it in block quotes. The Analysis section can interpret; the transcript section is sacred.
- ✅
"The ambition-to-lifespan ratio has never been more fucked" - ❌
User noted the tension between ambition and mortality
When to invoke
The user sends an audio or voice message via any channel (Telegram, voice
memo upload, openclaw audio attachment). The host agent typically provides
the transcript text. If not, transcribe via gbrain transcription (Groq
Whisper by default; OpenAI fallback for audio > 25MB segmented via ffmpeg).
The pipeline
1. STORE → Upload original audio to gbrain storage backend
(S3 / Supabase Storage / local — pluggable per
src/core/storage.ts).
2. TRANSCRIBE → Use the agent-provided transcript verbatim, OR call
gbrain transcription if no transcript was supplied.
3. ROUTE → Apply the decision tree (below) to find the right
destination directory.
4. WRITE → Create / update the destination brain page; preserve the
verbatim transcript in a block-quoted "User's Words"
section.
5. CROSS-LINK → For every entity mentioned (person, company), add a
timeline back-link from THEIR brain page to THIS one
(Iron Law per conventions/quality.md).
Decision tree (where the content goes)
Apply in order. First match wins. If multiple categories apply, file to the primary directory and cross-link to the others.
What ships with it
1 file 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.
- 10d ago First seen · 201 lines · 56 tokens per session scan A 69181602a77a
voice-note-ingest is a skill published in the GitHub repository cyberbird2048/gbrainmcp-clean (0 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 1,590 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to voice-note-ingest, differing in 10 lines, and is treated as a copy.
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