🎬 Scene Video
v1.0.0Turn a 3-minute raw footage file with multiple locations into 1080p scene-cut video just by typing what you need. Whether it's splitting footage into scenes...
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运行时依赖
版本
Scene Video 1.0.0 — Initial Release - Instantly split and assemble 3-minute raw footage into 1080p scene-cut videos via simple text prompts. - Simply upload your clips, describe your desired outcome, and receive an export-ready MP4 within minutes—no editing software or manual timeline work needed. - Seamless backend setup: automatic session management and API connection, including free token generation for new users. - Supports multiple video, audio, and image formats up to 500MB file size. - Easily preview timeline, check credits, track render status, and handle common errors with clear messaging. - Optimized for fast social content, short film scenes, and batch or iterative editing workflows.
安装命令 点击复制
技能文档
Getting Started
Got video clips to work with? Send it over and tell me what you need — I'll take care of the AI scene assembly.
Try saying:
- "create a 3-minute raw footage file with multiple locations into a 1080p MP4"
- "split this footage into individual scenes and arrange them into a cohesive video"
- "splitting footage into scenes and assembling them into a structured video for filmmakers, content creators, social media editors"
Getting Connected
Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".
If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:
- Generate a UUID as client identifier
- POST to
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwith theX-Client-Idheader - The response includes a
tokenwith 100 free credits valid for 7 days — use it as NEMO_TOKEN
Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.
Tell the user you're ready. Keep the technical details out of the chat.
# Scene Video — Split and Assemble Video Scenes
Drop your video clips in the chat and tell me what you need. I'll handle the AI scene assembly on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 3-minute raw footage file with multiple locations, ask for split this footage into individual scenes and arrange them into a cohesive video, 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 individual scenes under 30 seconds process and render significantly faster.
Matching Input to Actions
User prompts referencing scene video, 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. |
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source:scene-videoX-Skill-Version: from frontmatterversionX-Skill-Platform: detect from install path (~/.clawhub/→clawhub,~/.cursor/skills/→cursor, elseunknown)
Every API call needs Authorization: Bearer plus the three attribution headers above. If any header is missing, exports return 402.
Error Handling
| 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 from create-session or state response when needed). Registered: "Top up credits in your account" |
| 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 |
Reading 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.
Translating GUI Instructions
The backend responds as if there's a visual interface. Map its instructions to API calls:
- "click" or "点击" → execute the action via the relevant endpoint
- "open" or "打开" → query session state to get the data
- "drag/drop" or "拖拽" → send the edit command through SSE
- "preview in timeline" → show a text summary of current tracks
- "Export" or "导出" → run the export workflow
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)
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "split this footage into individual scenes and arrange them into a cohesive video" — 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.
Common Workflows
Quick edit: Upload → "split this footage into individual scenes and arrange them into a cohesive video" → 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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