edit YouTube video footage into highlight reel clips with this highlight-editor-youtube skill. Works with MP4, MOV, AVI, WebM files up to 500MB. YouTubers use it for extracting key highlight moments from long YouTube videos — processing takes 1-2 minutes on cloud GPUs and you get 1080p MP4 files.
Ready when you are. Drop your YouTube video footage here or describe what you want to make.
Try saying:
On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".
Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.
Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).
Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.
Confirm to the user you're connected and ready. Don't print tokens or raw JSON.
Send me your YouTube video footage and describe the result you want. The AI highlight extraction runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a 45-minute YouTube gaming stream, type "extract the best highlights and compile them into a 3-minute reel", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.
Worth noting: shorter source videos under 20 minutes process significantly faster.
User prompts referencing highlight editor youtube, 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 | ❌ |
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.
All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:
POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.GET /api/credits/balance/simple — returns available, frozen, total.GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source: highlight-editor-youtubeX-Skill-Version: from frontmatter versionX-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.
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)
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 |
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.
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=<id>, 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 onceThe backend processes faster when you're specific. Instead of "make it look better", try "extract the best highlights and compile them into a 3-minute reel" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.
Export as MP4 for widest compatibility across YouTube and social platforms.
Quick edit: Upload → "extract the best highlights and compile them into a 3-minute reel" → Download MP4. Takes 1-2 minutes 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.