Image To Video Dance Ai
by @vynbosserman65
Skip the learning curve of professional editing software. Describe what you want — make this photo dance to a hip-hop beat — and get dancing video clips back...
clawhub install image-to-video-dance-ai📖 About This Skill
name: image-to-video-dance-ai version: "1.0.0" displayName: "Image to Video Dance AI — Animate photos into dance videos" description: > Skip the learning curve of professional editing software. Describe what you want — make this photo dance to a hip-hop beat — and get dancing video clips back in 1-2 minutes. Upload JPG, PNG, WEBP, HEIC files up to 200MB, and the AI handles AI dance video generation automatically. Ideal for TikTok creators who want to create fun dance videos without filming themselves. metadata: {"openclaw": {"emoji": "💃", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}}
Getting Started
> Ready when you are. Drop your still images here or describe what you want to make.
Try saying:
Automatic Setup
On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".
Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.
Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: . The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).
Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.
Confirm to the user you're connected and ready. Don't print tokens or raw JSON.
Image to Video Dance AI — Animate photos into dance videos
Drop your still images in the chat and tell me what you need. I'll handle the AI dance video generation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a single portrait photo of a person, ask for make this photo dance to a hip-hop beat, 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 — clear front-facing photos with visible full body produce the most realistic dance animations.
Matching Input to Actions
User prompts referencing image to video dance ai, 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:
1. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":". Gives you a session_id.
2. Chat (SSE) — POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
3. Upload — POST /api/upload-video/nemo_agent/me/ — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/ — current draft and media info.
6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/ every 30s for completed status and download URL.
Formats: 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 image-to-video-dance-ai, 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).
Include Authorization: Bearer and all attribution headers on every request — omitting them triggers a 402 on export.
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=, registered users top up4001 — unsupported file type; show accepted formats4002 — file too large; suggest compressing or trimming400 — missing X-Client-Id; generate one and retry402 — free plan export blocked; not a credit issue, subscription tier429 — rate limited; wait 30s and retry onceCommon Workflows
Quick edit: Upload → "make this photo dance to a hip-hop beat" → 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 "make this photo dance to a hip-hop beat" — 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.
💡 Examples
> Ready when you are. Drop your still images here or describe what you want to make.
Try saying:
Automatic Setup
On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".
Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.
Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: . The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).
Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.
Confirm to the user you're connected and ready. Don't print tokens or raw JSON.
Image to Video Dance AI — Animate photos into dance videos
Drop your still images in the chat and tell me what you need. I'll handle the AI dance video generation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a single portrait photo of a person, ask for make this photo dance to a hip-hop beat, 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 — clear front-facing photos with visible full body produce the most realistic dance animations.