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vynbosserman65

Image To Video Dance Ai

by vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install image-to-video-dance-ai
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...
README (SKILL.md)

Getting Started

Ready when you are. Drop your still images here or describe what you want to make.

Try saying:

  • "animate a single portrait photo of a person into a 1080p MP4"
  • "make this photo dance to a hip-hop beat"
  • "animating photos of people into dancing videos for TikTok creators"

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: \x3Cuuid>. 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. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. 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. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> 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 \x3CNEMO_TOKEN> 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 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=\x3Cid>, 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

Common 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.

Usage Guidance
This skill appears to do exactly what it says (upload photos to a remote API to generate dance videos) and only asks for a single API token. However: 1) the publisher/source is unknown and there's no homepage or privacy policy—ask the publisher for a privacy/security page before uploading images of people; 2) clarify the metadata inconsistency: SKILL.md references ~/.config/nemovideo/ but the registry lists no config paths—ask whether the skill will read or write local config files and where anonymous tokens/session data are stored; 3) the skill will send your images to https://mega-api-prod.nemovideo.ai — if those images are sensitive, do not proceed; 4) prefer short‑lived/anonymous tokens (the skill supports creating one) and avoid setting long‑lived credentials unless you trust the service; 5) if you need stronger assurance, request the skill maintainer's homepage, a privacy policy, or source code so you can audit network/IO behavior. If you choose to install anyway, monitor network traffic for unexpected endpoints and avoid using high‑privilege credentials with this skill.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-dance-ai Version: 1.0.0 The skill is a legitimate integration for an AI video generation service hosted at nemovideo.ai. It provides instructions for the agent to manage API sessions, upload images, and poll for video rendering status. It follows security best practices by instructing the agent not to expose tokens in the chat and limits its scope to the declared NEMO_TOKEN and service-specific endpoints.
Capability Assessment
Purpose & Capability
The name/description (animate photos into dance videos) align with the SKILL.md which instructs uploading images and calling a remote rendering API. Requiring a NEMO_TOKEN for API calls is expected. However, the SKILL.md frontmatter requests a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths, which is an inconsistency worth clarifying. The skill's source and homepage are unknown.
Instruction Scope
The instructions stay within the stated purpose: create/get an auth token, open a session, upload images, use SSE for edits, poll for export and return download URLs. It does not instruct reading arbitrary local files or unrelated credentials. It does instruct deriving an X-Skill-Platform header from install paths (mentions ~/.clawhub/ and ~/.cursor/skills/), which implies inspecting environment/paths — the SKILL.md does not explicitly tell the agent to read other local files, but this header derivation could require checking agent runtime paths.
Install Mechanism
No install spec or code files are present (instruction-only). That minimizes disk persistence and install-time risk.
Credentials
Only one credential is declared (primaryEnv = NEMO_TOKEN), which is appropriate for a cloud API client. The SKILL.md frontmatter also lists a config path (~/.config/nemovideo/) not declared in the registry summary; it's unclear whether the skill will attempt to read that local config directory. Confirm whether the skill reads or writes local config files and how it stores anonymous tokens/session data.
Persistence & Privilege
The skill is not always-enabled and has no install step. It asks to save transient session_id and to store an anonymouse token if created, which is normal for sessioned API use. It does not request system-wide privileges or modify other skills' configs.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-dance-ai
  3. After installation, invoke the skill by name or use /image-to-video-dance-ai
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Image to Video Dance AI. - Instantly animates uploaded photos into dance videos using cloud AI. - Supports JPG, PNG, WEBP, HEIC files up to 200MB; generates 1080p MP4 videos in 1–2 minutes. - Simple setup: automatic anonymous token generation and session handling. - Core actions include uploading images, generating dance videos, checking credits, and exporting finished clips. - Designed for creators who want quick, realistic dance video results without complex editing.
Metadata
Slug image-to-video-dance-ai
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Image To Video Dance Ai?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 63 downloads so far.

How do I install Image To Video Dance Ai?

Run "/install image-to-video-dance-ai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Image To Video Dance Ai free?

Yes, Image To Video Dance Ai is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Image To Video Dance Ai support?

Image To Video Dance Ai is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Image To Video Dance Ai?

It is built and maintained by vynbosserman65 (@vynbosserman65); the current version is v1.0.0.

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