walkie-talkie-modeHandles voice-to-voice conversations on WhatsApp. Automatically transcribes incoming audio and responds with local TTS audio. Use when the user wants to "talk" instead of type.
Install via ClawdBot CLI:
clawdbot install rubenfb23/walkie-talkie-modeGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 20, 2026
Enables businesses to handle customer inquiries via voice messages on WhatsApp, automatically transcribing and responding with audio. This reduces typing effort and provides a more personal touch, ideal for support teams managing high volumes of queries.
Facilitates voice-based conversations among distributed teams using WhatsApp, allowing quick audio updates and responses without switching apps. It enhances collaboration by mimicking walkie-talkie functionality, suitable for field workers or remote offices.
Supports language learners by transcribing their spoken attempts and providing audio feedback via TTS, creating an interactive voice loop. This helps improve pronunciation and listening skills in a conversational context on a familiar platform.
Assists users with visual impairments by enabling voice-to-voice interactions on WhatsApp, automatically handling audio input and output. This makes digital communication more accessible without relying on text, enhancing inclusivity.
Allows organizations to send automated voice responses for alerts or updates, such as appointment reminders or order confirmations, via WhatsApp. It leverages local TTS for quick, reliable audio delivery without external APIs.
Offer this skill as a subscription service for businesses to integrate into their WhatsApp customer support, charging monthly fees based on usage volume. Revenue comes from tiered plans that scale with transcription and TTS processing needs.
Provide a free version with basic voice-to-voice functionality and limited usage, then upsell premium features like faster response times, custom TTS voices, or advanced analytics. This attracts individual users and small teams before converting them to paid plans.
License the skill to enterprises or developers for embedding into their own applications, such as internal communication tools or customer service platforms. Revenue is generated through one-time licensing fees or annual contracts for customization and support.
💬 Integration Tip
Ensure local tools like ffmpeg and whisper-cpp are properly installed and configured for fast audio processing to meet RTF constraints; test with various audio formats to avoid compatibility issues.
Scored Apr 19, 2026
Local speech-to-text with the Whisper CLI (no API key).
Local speech-to-text using OpenAI Whisper. Runs fully offline after model download. High quality transcription with multiple model sizes.
Text-to-speech via OpenAI Audio Speech API.
Generate spoken audio from text using the local Kokoro TTS engine. Use when the user asks to "say" something, requests a voice message, or wants text converted to speech.
Convert text to speech using Hume AI (or OpenAI) API. Use when the user asks for an audio message, a voice reply, or to hear something "of vive voix".
Speech-To-Text with MLX (Apple Silicon) and opensource models (default GLM-ASR-Nano-2512) locally.