nanoclaw-gmail: Skill for Claude Code

.claude/skills/use-local-whisper/SKILL.md

use-local-whisper is a skill for Claude Code from nanocoai/nanoclaw-gmail. It costs 46 tokens per session (1,286 once invoked), scanned A, a copy of use-local-whisper, MIT.

A setup procedure that changes voice transcription from OpenAI’s Whisper API to whisper.cpp running locally on Apple Silicon Macs. Voice transcription turns spoken audio into text.

In plain words
What is it for?
Use it to transcribe WhatsApp voice messages locally, provided the voice-transcription setup, whisper.cpp, ffmpeg, and a speech-recognition model are installed.
Why use it?
It keeps audio processing on the device, avoiding an API key, network requests, and API charges.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is nanocoai/nanoclaw-gmail's own configuration. It tells Claude Code how to work on nanoclaw-gmail itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything nanoclaw-gmail configures →

Reuse

Borrowing it

Nothing to install: this file belongs to nanocoai/nanoclaw-gmail. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/nanocoai/nanoclaw-gmail/main/.claude/skills/use-local-whisper/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/nanocoai/nanoclaw-gmail

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,286 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.01286
Opus 5 $0.00023 $0.00643
Sonnet 5 $0.00009 $0.00257
Haiku 4.5 $0.00005 $0.00129

Measured 11d ago against content hash d43b570be974, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 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 -L -o data/models/ggml-base.bin "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"
Origin

This is a copy

92% identical to use-local-whisper — 16 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.

.claude/skills/use-local-whisper/SKILL.md · 153 lines

How it starts

The opening of the file, as written. The whole thing — 153 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-transcription skill must be applied first (WhatsApp channel)
  • macOS with Apple Silicon (M1+) recommended
  • whisper-cpp installed: brew install whisper-cpp (provides the whisper-cli binary)
  • ffmpeg installed: 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

Ensure WhatsApp fork remote

git remote -v

If whatsapp is missing, add it:

git remote add whatsapp https://github.com/qwibitai/nanoclaw-whatsapp.git

Read the full file on GitHub · 153 lines

Changes

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.

  1. 11d ago First seen · 153 lines · 46 tokens per session scan A d43b570be974

Subscribe to this mod's changes

use-local-whisper is a skill published in the GitHub repository nanocoai/nanoclaw-gmail (2 stars, last pushed 5mo ago), licensed MIT. It adds 46 tokens to every session and 1,286 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 92% identical to use-local-whisper, differing in 16 lines, and is treated as a copy.

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