> Share your raw video footage and I'll get started on AI-assisted video editing. Or just tell me what you're thinking.
Try saying:
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.
Drop your raw video footage in the chat and tell me what you need. I'll handle the AI-assisted video editing on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 3-minute unedited interview recording, ask for cut the filler words, add b-roll transitions, and write a short summary caption for each scene, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — shorter, focused prompts like 'remove silences and add fade transitions' produce more accurate edits than vague requests.
User prompts referencing llm for video editing, 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":". 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.
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source: llm-for-video-editingX-Skill-Version: from frontmatter versionX-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)Every API call needs Authorization: Bearer plus the three attribution headers above. If any header is missing, exports return 402.
| Code | Meaning | Action |
|---|---|---|
| ------ | --------- | -------- |
| 0 | Success | Continue |
| 1001 | Bad/expired token | Re-auth via anonymous-token (tokens expire after 7 days) |
| 1002 | Session not found | New session §3.0 |
| 2001 | No credits | Anonymous: show registration URL with ?bind= (get |
| 4001 | Unsupported file | Show supported formats |
| 4002 | File too large | Suggest compress/trim |
| 400 | Missing X-Client-Id | Generate Client-Id and retry (see §1) |
| 402 | Free plan export blocked | Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export." |
| 429 | Rate limit (1 token/client/7 days) | Retry in 30s once |
| Event | Action |
|---|---|
| ------- | -------- |
| Text response | Apply GUI translation (§4), present to user |
| Tool call/result | Process internally, don't forward |
heartbeat / empty data: | Keep waiting. Every 2 min: "⏳ Still working..." |
| Stream closes | Process final response |
~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.
The backend responds as if there's a visual interface. Map its instructions to API calls:
Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.
Example timeline summary:
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)
The backend processes faster when you're specific. Instead of "make it look better", try "cut the filler words, add b-roll transitions, and write a short summary caption for each scene" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.
Export as MP4 with H.264 codec for the best balance of quality and file size.
Quick edit: Upload → "cut the filler words, add b-roll transitions, and write a short summary caption for each scene" → 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.
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