Getting Started
Send me your raw video footage and I'll handle the AI tutorial video creation. Or just describe what you're after.
Try saying:
- "create a 10-minute screen recording walkthrough into a 1080p MP4"
- "add chapter titles, highlight clicks, and insert a summary slide at the end"
- "turning screen recordings into structured lesson videos with titles and captions for educators and online course creators"
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.
Tutor Video — Create and Export Lesson Videos
Send me your raw video footage and describe the result you want. The AI tutorial video creation runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a 10-minute screen recording walkthrough, type "add chapter titles, highlight clicks, and insert a summary slide at the end", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.
Worth noting: breaking your content into short segments under 5 minutes each produces cleaner chapter detection.
Matching Input to Actions
User prompts referencing tutor 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.
All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:
- Session —
POST /api/tasks/me/with-session/nemo_agentwith{"task_name":"project","language":"<lang>"}. Gives you asession_id. - Chat (SSE) —
POST /run_ssewithsession_idand your message innew_message.parts[0].text. SetAccept: text/event-stream. Up to 15 min. - Upload —
POST /api/upload-video/nemo_agent/me/<sid>— multipart file or JSON with URLs. - Credits —
GET /api/credits/balance/simple— returnsavailable,frozen,total. - State —
GET /api/state/nemo_agent/me/<sid>/latest— current draft and media info. - Export —
POST /api/render/proxy/lambdawith render ID and draft JSON. PollGET /api/render/proxy/lambda/<id>every 30s forcompletedstatus and download URL.
Formats: 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 | tutor-video |
| X-Skill-Version | frontmatter version |
| X-Skill-Platform | auto-detect: clawhub / cursor / unknown from install path |
Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.
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)
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 |
SSE Event Handling
| 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.
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=<id>, registered users top up4001— unsupported file type; show accepted formats4002— file too large; suggest compressing or trimming400— missingX-Client-Id; generate one and retry402— free plan export blocked; not a credit issue, subscription tier429— rate limited; wait 30s and retry once
Common Workflows
Quick edit: Upload → "add chapter titles, highlight clicks, and insert a summary slide at the end" → 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.
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "add chapter titles, highlight clicks, and insert a summary slide at the end" — 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 learning platforms like Teachable and Udemy.
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