Getting Started
Send me your text prompts and I'll handle the AI video generation. Or just describe what you're after.
Try saying:
- "generate a short text description of a scene or idea into a 1080p MP4"
- "generate a 30-second video of a sunset over mountains with calm background music"
- "generating short videos from text prompts for free for content creators"
First-Time Connection
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.
- Obtain a free token: Generate a random UUID as client identifier. POST to
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwith headerX-Client-Idset to that UUID. The responsedata.tokenis your NEMO_TOKEN — 100 free credits, valid 7 days. - Create a session: POST to
https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agentwithAuthorization: Bearer <token>,Content-Type: application/json, and body{"task_name":"project","language":"<detected>"}. Store the returnedsession_idfor all subsequent requests.
Keep setup communication brief. Don't display raw API responses or token values to the user.
Video Generator Free Like Grok — Generate Videos from Text Prompts
Send me your text prompts and describe the result you want. The AI video generation runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a short text description of a scene or idea, type "generate a 30-second video of a sunset over mountains with calm background music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.
Worth noting: shorter and more specific prompts produce better results than vague long descriptions.
Matching Input to Actions
User prompts referencing video generator free like grok, 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.
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source:video-generator-free-like-grokX-Skill-Version: from frontmatterversionX-Skill-Platform: detect from install path (~/.clawhub/→clawhub,~/.cursor/skills/→cursor, elseunknown)
Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.
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)
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
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "generate a 30-second video of a sunset over mountains with calm background music" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, WebM, GIF for the smoothest experience.
Export as MP4 for widest compatibility across social platforms.
Common Workflows
Quick edit: Upload → "generate a 30-second video of a sunset over mountains with calm background music" → 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.