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 sliamh11/Deus --skill use-local-whispergit clone --depth 1 https://github.com/sliamh11/DeusWrote 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/sliamh11/deus/use-local-whisper)<a href="https://agentmods.dev/skills/sliamh11/deus/use-local-whisper"><img src="https://agentmods.dev/badge/skills/sliamh11/deus/use-local-whisper/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/sliamh11/deus/use-local-whisper"><img src="https://agentmods.dev/badge/skills/sliamh11/deus/use-local-whisper.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 | $0.00046 | $0.01251 |
| Opus 5.5 | $0.00018 | $0.00500 |
| Sonnet 5.5 | $0.00009 | $0.00250 |
| Haiku 4.5 | $0.00005 | $0.00125 |
Grade A, and why
use-local-whisper 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 1mo 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 -L -o data/models/ggml-base.bin "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin" This is a copy
92% identical to use-local-whisper — 37 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use Local Whisper
Switches voice transcription from OpenAI's Whisper API to local whisper.cpp. Runs entirely on-device — no API key, no network, no cost.
Channel support: Currently WhatsApp only. The transcription module (src/transcription.ts) uses Baileys types for audio download. Other channels (Telegram, Discord, etc.) would need their own audio-download logic before this skill can serve them.
Note: The Homebrew package is whisper-cpp, but the CLI binary it installs is whisper-cli.
Prerequisites
voice-transcriptionskill must be applied first (WhatsApp channel)- macOS with Apple Silicon (M1+) recommended
whisper-cppinstalled:brew install whisper-cpp(provides thewhisper-clibinary)ffmpeginstalled:brew install ffmpeg- A GGML model file downloaded to
data/models/
Phase 1: Pre-flight
Check if already applied
Check if src/transcription.ts already uses whisper-cli:
grep 'whisper-cli' src/transcription.ts && echo "Already applied" || echo "Not applied"
If already applied, skip to Phase 3 (Verify).
Check dependencies are installed
whisper-cli --help >/dev/null 2>&1 && echo "WHISPER_OK" || echo "WHISPER_MISSING"
ffmpeg -version >/dev/null 2>&1 && echo "FFMPEG_OK" || echo "FFMPEG_MISSING"
If missing, install via Homebrew:
brew install whisper-cpp ffmpeg
Check for model file
ls data/models/ggml-*.bin 2>/dev/null || echo "NO_MODEL"
If no model exists, download the base model (148MB, good balance of speed and accuracy):
mkdir -p data/models
curl -L -o data/models/ggml-base.bin "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"
For better accuracy at the cost of speed, use ggml-small.bin (466MB) or ggml-medium.bin (1.5GB).
Phase 2: Apply Code Changes
The local whisper feature modifies src/transcription.ts to use the whisper-cli binary instead of the OpenAI API. Check if it's already applied:
grep 'whisper-cli' src/transcription.ts && echo "Already applied" || echo "Not applied"
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.
- 1mo ago First seen · 136 lines · 46 tokens per session scan A dbdf9e977265
use-local-whisper is a skill published in the GitHub repository sliamh11/Deus (52 stars, last pushed 3d ago), licensed MIT. It adds 46 tokens to every session and 1,251 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 92% identical to use-local-whisper, differing in 37 lines, and is treated as a copy.
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