
Audio Reply
- 22 installs
- 638 repo stars
- Updated March 7, 2026
- sundial-org/awesome-openclaw-skills
Helps with ai & agent building tasks during AI-assisted development.
About
audio-reply is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.
- audio-reply
- AI & Agent Building
- AI-coding skill
Audio Reply by the numbers
- 22 all-time installs (skills.sh)
- Ranked #10,168 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 22 |
|---|---|
| repo stars | ★ 638 |
| Last updated | March 7, 2026 |
| Repository | sundial-org/awesome-openclaw-skills ↗ |
What it does
Helps with ai & agent building tasks during AI-assisted development.
Files
Audio Reply Skill
Generate spoken audio responses using MLX Audio TTS (chatterbox-turbo model).
Trigger Phrases
- "read it to me [URL]" - Fetch content from URL and read it aloud
- "talk to me [topic/question]" - Generate a conversational response as audio
- "speak", "say it", "voice reply" - Convert your response to audio
How to Use
Mode 1: Read URL Content
User: read it to me https://example.com/article1. Fetch the URL content using WebFetch 2. Extract readable text (strip HTML, focus on main content) 3. Generate audio using TTS 4. Play the audio and delete the file afterward
Mode 2: Conversational Audio Response
User: talk to me about the weather today1. Generate a natural, conversational response 2. Keep it concise (TTS works best with shorter segments) 3. Convert to audio, play it, then delete the file
Implementation
TTS Command
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Your text here" \
--play \
--file_prefix /tmp/audio_replyKey Parameters
--model mlx-community/chatterbox-turbo-fp16- Fast, natural voice--play- Auto-play the generated audio--file_prefix- Save to temp location for cleanup--exaggeration 0.3- Optional: add expressiveness (0.0-1.0)--speed 1.0- Adjust speech rate if needed
Text Preparation Guidelines
For "read it to me" mode: 1. Fetch URL with WebFetch tool 2. Extract main content, strip navigation/ads/boilerplate 3. Summarize if very long (>500 words) - keep key points 4. Add natural pauses with periods and commas
For "talk to me" mode: 1. Write conversationally, as if speaking 2. Use contractions (I'm, you're, it's) 3. Add filler words sparingly for naturalness ([chuckle], um, anyway) 4. Keep responses under 200 words for best quality 5. Avoid technical jargon unless explaining it
Audio Generation & Cleanup (IMPORTANT)
Always delete the audio file after playing - it's already in the chat history.
# Generate with unique filename and play
OUTPUT_FILE="/tmp/audio_reply_$(date +%s)"
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Your response text" \
--play \
--file_prefix "$OUTPUT_FILE"
# ALWAYS clean up after playing
rm -f "${OUTPUT_FILE}"*.wav 2>/dev/nullError Handling
If TTS fails: 1. Check if model is downloaded (first run downloads ~500MB) 2. Ensure uv is installed and in PATH 3. Fall back to text response with apology
Example Workflows
Example 1: Read URL
User: read it to me https://blog.example.com/new-feature
Assistant actions:
1. WebFetch the URL
2. Extract article content
3. Generate TTS:
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Here's what I found... [article summary]" \
--play --file_prefix /tmp/audio_reply_1706123456
4. Delete: rm -f /tmp/audio_reply_1706123456*.wav
5. Confirm: "Done reading the article to you."Example 2: Talk to Me
User: talk to me about what you can help with
Assistant actions:
1. Generate conversational response text
2. Generate TTS:
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Hey! So I can help you with all kinds of things..." \
--play --file_prefix /tmp/audio_reply_1706123789
3. Delete: rm -f /tmp/audio_reply_1706123789*.wav
4. (No text output needed - audio IS the response)Notes
- First run may take longer as the model downloads (~500MB)
- Audio quality is best for English; other languages may vary
- For long content, consider chunking into multiple audio segments
- The
--playflag uses system audio - ensure volume is up