openai-whisper
Local speech-to-text with the Whisper CLI (no API key).
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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Local speech-to-text with the Whisper CLI (no API key).
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Connect AssistClaw to a Bee wearable via BeeMCP (MCP server) without using bee CLI/proxy. Use when: BeeMCP is already installed or user wants Bee tools exposed through MCP lazy-loading.
Query and control a Bee wearable (bee.computer) — conversations, facts, todos, journals, daily briefs, and real-time event streams. Use when: user references their Bee device, asks what they just talked about, wants a daily brief, manages facts/todos captured by Bee, or searches their personal lifelog. NOT for: generic calendar/reminder apps, historical data older than the Bee account, or non-Bee wearables.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
Manage Apple Notes via the `memo` CLI on macOS (create, view, edit, delete, search, move, and export notes). Use when a user asks AssistClaw to add a note, list notes, search notes, or manage note folders.
Manage Apple Reminders via remindctl CLI (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.
Create, search, and manage Bear notes via grizzly CLI.
| name | openai-whisper |
| description | Local speech-to-text with the Whisper CLI (no API key). |
| homepage | https://openai.com/research/whisper |
| metadata | {"assistclaw":{"emoji":"🎙️","requires":{"bins":["whisper"]},"install":[{"id":"brew","kind":"brew","formula":"openai-whisper","bins":["whisper"],"label":"Install OpenAI Whisper (brew)"}]}} |
Use whisper to transcribe audio locally.
Quick start
whisper /path/audio.mp3 --model medium --output_format txt --output_dir .whisper /path/audio.m4a --task translate --output_format srtNotes
~/.cache/whisper on first run.--model defaults to turbo on this install.