Skip the learning curve of professional editing software. Describe what you want — turn these images into a YouTube video with music and transitions — and ge...
---
name: youtube-image-to-video
version: "1.0.0"
displayName: "YouTube Image to Video — Convert Images Into YouTube Videos"
description: >
Skip the learning curve of professional editing software. Describe what you want — turn these images into a YouTube video with music and transitions — and get YouTube-ready video back in 1-2 minutes. Upload JPG, PNG, WEBP, HEIC files up to 200MB, and the AI handles AI video creation automatically. Ideal for YouTubers who want to create videos from photos without editing software.
metadata: {"openclaw": {"emoji": "🖼️", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}
---
## Getting Started
> Share your images and I'll get started on AI video creation. Or just tell me what you're thinking.
**Try saying:**
- "convert my images"
- "export 1080p MP4"
- "turn these images into a YouTube"
### 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-token` with the `X-Client-Id` header
- The response includes a `token` with 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.
# YouTube Image to Video — Convert Images Into YouTube Videos
This tool takes your images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.
Say you have five landscape photos from a YouTube travel vlog and want to turn these images into a YouTube video with music and transitions — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.
Tip: using 10 or fewer images keeps transitions smooth and processing fast.
## Matching Input to Actions
User prompts referencing youtube image to 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":"<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.
Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `youtube-image-to-video`, `X-Skill-Version` comes from the `version` field, and `X-Skill-Platform` is detected from the install path (`~/.clawhub/` = `clawhub`, `~/.cursor/skills/` = `cursor`, otherwise `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.
### Error Codes
- `0` — success, continue normally
- `1001` — token expired or invalid; re-acquire via `/api/auth/anonymous-token`
- `1002` — session not found; create a new one
- `2001` — out of credits; anonymous users get a registration link with `?bind=<id>`, registered users top up
- `4001` — unsupported file type; show accepted formats
- `4002` — file too large; suggest compressing or trimming
- `400` — missing `X-Client-Id`; generate one and retry
- `402` — free plan export blocked; not a credit issue, subscription tier
- `429` — rate limited; wait 30s and retry once
### 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.
### 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 "turn these images into a YouTube video with music and transitions" — concrete instructions get better results.
Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.
Export as MP4 for widest compatibility with YouTube uploads.
## Common Workflows
**Quick edit**: Upload → "turn these images into a YouTube video with music and transitions" → 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.
don't have the plugin yet? install it then click "run inline in claude" again.