Install
openclaw skills install a-video-usingSkip the learning curve of professional editing software. Describe what you want — trim the intro, add background music, and export as a highlight reel — and...
openclaw skills install a-video-usingShare your video clips and I'll get started on AI video creation. Or just tell me what you're thinking.
Try saying:
When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").
Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.Keep setup communication brief. Don't display raw API responses or token values to the user.
Send me your video clips and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a 2-minute raw screen recording, type "trim the intro, add background music, and export as a highlight reel", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.
Worth noting: shorter source clips under 3 minutes process significantly faster.
User prompts referencing a video using, 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.
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":"<lang>"}. 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/<sid> | POST | Upload a file (multipart) or URL. |
/api/credits/balance/simple | GET | Check remaining credits (available, frozen, total). |
/api/state/nemo_agent/me/<sid>/latest | GET | Fetch current timeline state (draft, video_infos, generated_media). |
/api/render/proxy/lambda | POST | Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s. |
Accepted file types: 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: a-video-usingX-Skill-Version: from frontmatter versionX-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.
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 onceText 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.
The backend responds as if there's a visual interface. Map its instructions to API calls:
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)
Quick edit: Upload → "trim the intro, add background music, and export as a highlight 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.
The backend processes faster when you're specific. Instead of "make it look better", try "trim the intro, add background music, and export as a highlight 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 platforms.