Video To Audio
by @mory128
Skip the learning curve of professional editing software. Describe what you want — extract the audio track from my video as an MP3 file — and get extracted a...
clawhub install video-to-audio📖 About This Skill
name: video-to-audio version: "1.0.0" displayName: "Video to Audio — Extract Audio from Video Files" description: > Skip the learning curve of professional editing software. Describe what you want — extract the audio track from my video as an MP3 file — and get extracted audio files back in 20-40 seconds. Upload MP4, MOV, AVI, WebM files up to 500MB, and the AI handles audio extraction automatically. Ideal for podcasters, content creators, educators who want the audio from a video without re-recording or editing software. metadata: {"openclaw": {"emoji": "🎵", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}
Getting Started
> Share your video files and I'll get started on audio extraction. Or just tell me what you're thinking.
Try saying:
Quick Start Setup
This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").
Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id headerdata.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.
Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.
Video to Audio — Extract Audio from Video Files
Send me your video files and describe the result you want. The audio extraction runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a 3-minute MP4 interview recording, type "extract the audio track from my video as an MP3 file", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.
Worth noting: shorter clips process faster and produce cleaner audio output.
Matching Input to Actions
User prompts referencing video to audio, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.
| User says... | Action | Skip SSE? | |-------------|--------|----------| | "export" / "导出" / "download" / "send me the video" | → §3.5 Export | ✅ | | "credits" / "积分" / "balance" / "余额" | → §3.3 Credits | ✅ | | "status" / "状态" / "show tracks" | → §3.4 State | ✅ | | "upload" / "上传" / user sends file | → §3.2 Upload | ✅ | | Everything else (generate, edit, add BGM…) | → §3.1 SSE | ❌ |
Cloud Render Pipeline Details
Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.
Base URL: https://mega-api-prod.nemovideo.ai
| Endpoint | Method | Purpose |
|----------|--------|---------|
| /api/tasks/me/with-session/nemo_agent | POST | Start a new editing session. Body: {"task_name":"project","language":". Returns session_id. |
| /run_sse | POST | Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min. |
| /api/upload-video/nemo_agent/me/ | POST | Upload a file (multipart) or URL. |
| /api/credits/balance/simple | GET | Check remaining credits (available, frozen, total). |
| /api/state/nemo_agent/me/ | GET | Fetch current timeline state (draft, video_infos, generated_media). |
| /api/render/proxy/lambda | POST | Start export. Body: {"id":"render_. Poll status every 30s. |
Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
Three attribution headers are required on every request and must match this file's frontmatter:
| Header | Value |
|--------|-------|
| X-Skill-Source | video-to-audio |
| X-Skill-Version | frontmatter version |
| X-Skill-Platform | auto-detect: clawhub / cursor / unknown from install path |
Every API call needs Authorization: Bearer plus the three attribution headers above. If any header is missing, exports return 402.
Error Codes
0 — success, continue normally1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token1002 — session not found; create a new one2001 — out of credits; anonymous users get a registration link with ?bind=, registered users top up4001 — unsupported file type; show accepted formats4002 — file too large; suggest compressing or trimming400 — missing X-Client-Id; generate one and retry402 — free plan export blocked; not a credit issue, subscription tier429 — rate limited; wait 30s and retry onceReading the SSE Stream
Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.
About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.
Backend Response Translation
The backend assumes a GUI exists. Translate these into API actions:
| Backend says | You do | |-------------|--------| | "click [button]" / "点击" | Execute via API | | "open [panel]" / "打开" | Query session state | | "drag/drop" / "拖拽" | Send edit via SSE | | "preview in timeline" | Show track summary | | "Export button" / "导出" | Execute export workflow |
Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "extract the audio track from my video as an MP3 file" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.
MP4 source files give the most reliable audio extraction results.
Common Workflows
Quick edit: Upload → "extract the audio track from my video as an MP3 file" → Download MP4. Takes 20-40 seconds for a 30-second clip.
Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.
Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.
💡 Examples
> Share your video files and I'll get started on audio extraction. Or just tell me what you're thinking.
Try saying:
Quick Start Setup
This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").
Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id headerdata.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.
Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.
Video to Audio — Extract Audio from Video Files
Send me your video files and describe the result you want. The audio extraction runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a 3-minute MP4 interview recording, type "extract the audio track from my video as an MP3 file", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.
Worth noting: shorter clips process faster and produce cleaner audio output.