Skills ai-image-to-video-best
git clone https://github.com/openclaw/skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bwbernardweston18/ai-image-to-video-best" ~/.claude/skills/openclaw-skills-ai-image-to-video-best && rm -rf "$T"
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/bwbernardweston18/ai-image-to-video-best" ~/.openclaw/skills/openclaw-skills-ai-image-to-video-best && rm -rf "$T"
skills/bwbernardweston18/ai-image-to-video-best/SKILL.mdGetting Started
Share your static images and I'll get started on AI video creation. Or just tell me what you're thinking.
Try saying:
- "convert my static images"
- "export 1080p MP4"
- "turn these images into a smooth"
Quick Start Setup
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:
- Generate a UUID as client identifier
- POST
withhttps://mega-api-prod.nemovideo.ai/api/auth/anonymous-token
headerX-Client-Id - Extract
from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)data.token
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.
AI Image to Video — Convert Images Into Video Clips
This tool takes your static images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.
Say you have three product photos in JPG format and want to turn these images into a smooth animated video with transitions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.
Tip: high-contrast images with clear subjects animate more smoothly.
Matching Input to Actions
User prompts referencing ai image to video best, 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 —
withPOST /api/tasks/me/with-session/nemo_agent
. Gives you a{"task_name":"project","language":"<lang>"}
.session_id - Chat (SSE) —
withPOST /run_sse
and your message insession_id
. Setnew_message.parts[0].text
. Up to 15 min.Accept: text/event-stream - Upload —
— multipart file or JSON with URLs.POST /api/upload-video/nemo_agent/me/<sid> - Credits —
— returnsGET /api/credits/balance/simple
,available
,frozen
.total - State —
— current draft and media info.GET /api/state/nemo_agent/me/<sid>/latest - Export —
with render ID and draft JSON. PollPOST /api/render/proxy/lambda
every 30s forGET /api/render/proxy/lambda/<id>
status and download URL.completed
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 |
|---|---|
| |
| frontmatter |
| auto-detect: / / from install path |
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.
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)
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
SSE Event Handling
| Event | Action |
|---|---|
| Text response | Apply GUI translation (§4), present to user |
| Tool call/result | Process internally, don't forward |
/ empty | 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
— success, continue normally0
— token expired or invalid; re-acquire via1001/api/auth/anonymous-token
— session not found; create a new one1002
— out of credits; anonymous users get a registration link with2001
, registered users top up?bind=<id>
— unsupported file type; show accepted formats4001
— file too large; suggest compressing or trimming4002
— missing400
; generate one and retryX-Client-Id
— free plan export blocked; not a credit issue, subscription tier402
— rate limited; wait 30s and retry once429
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "turn these images into a smooth animated video with 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 across social platforms.
Common Workflows
Quick edit: Upload → "turn these images into a smooth animated video with transitions" → Download MP4. Takes 30-60 seconds 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.