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vynbosserman65

Image To Video Motion Control

by vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install image-to-video-motion-control
Description
convert images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 50MB. marketers, social media creators, filmmakers use...
README (SKILL.md)

Getting Started

Send me your images and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

  • "convert a single product photo or illustration into a 1080p MP4"
  • "animate this image with a slow zoom-in and leftward pan"
  • "turning still images into moving video clips with controlled camera motion for marketers, social media creators, filmmakers"

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.

Image to Video Motion Control — Animate Images with Controlled Motion

Send me your images and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a single product photo or illustration, type "animate this image with a slow zoom-in and leftward pan", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: simpler backgrounds produce smoother motion results with fewer artifacts.

Matching Input to Actions

User prompts referencing image to video motion control, 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.

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source image-to-video-motion-control
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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)

Common Workflows

Quick edit: Upload → "animate this image with a slow zoom-in and leftward pan" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate this image with a slow zoom-in and leftward pan" — concrete instructions get better results.

Max file size is 50MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Use PNG images for best quality since lossless input reduces motion blur artifacts.

Usage Guidance
This skill will upload any images you send to https://mega-api-prod.nemovideo.ai and will use a NEMO_TOKEN (it will also try to obtain an anonymous token if none is present). Before installing or using it: (1) Don't upload sensitive or private images unless you trust the service and its privacy terms. (2) Prefer supplying your own NEMO_TOKEN (from an account you control) rather than relying on an anonymous token if you need access control. (3) Ask the publisher to resolve the metadata mismatch about ~/.config/nemovideo/ — confirm whether the skill will read local config files. (4) Note the owner is unknown and there is no homepage; exercise caution and verify the service independently before sending confidential data.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-motion-control Version: 1.0.0 The skill provides instructions for an AI agent to interface with the NemoVideo API (mega-api-prod.nemovideo.ai) for image-to-video generation. It outlines standard API interaction patterns, including authentication via NEMO_TOKEN or anonymous token generation, multipart file uploads, and polling for render status. The instructions in SKILL.md are focused on functional task completion, error handling, and UI/UX translation, with no evidence of data exfiltration, malicious execution, or harmful prompt injection.
Capability Assessment
Purpose & Capability
Name, description, and runtime instructions consistently describe sending images to a remote GPU-based renderer (mega-api-prod.nemovideo.ai) and returning MP4s. Requesting a NEMO_TOKEN credential is proportionate for calling that API.
Instruction Scope
SKILL.md precisely instructs the agent to create sessions, upload files (multipart or by URL), stream SSE, poll render status, and include attribution headers — all consistent with a cloud render workflow. This necessarily transmits user images and edits to an external service; that is expected behavior but is a privacy/data-exfiltration risk the user should understand.
Install Mechanism
No install spec and no code files — instruction-only skill. Lowest install risk (nothing to write to disk or execute locally).
Credentials
The skill declares a single primary credential NEMO_TOKEN which fits the API usage. However, SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) while the registry metadata shows no required config paths — this inconsistency could mean the skill expects to read a local config (potentially containing tokens) that was not declared. The skill also describes obtaining anonymous tokens automatically if no token is present, which means it will make network calls to acquire and use credentials without explicit user-provided secrets.
Persistence & Privilege
always:false and no install actions; skill does not request persistent system-wide privileges or try to modify other skills. Autonomous invocation is allowed (platform default) but not combined with other high privileges.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-motion-control
  3. After installation, invoke the skill by name or use /image-to-video-motion-control
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Version 1.0.0 — Initial release - Launches image-to-video motion control skill: turn still images into animated 1080p MP4 clips with AI-driven, controlled camera motion. - Supports JPG, PNG, WEBP, HEIC images up to 50MB; delivers results in 30–60 seconds using cloud GPUs. - Handles uploads, animation requests, video export, credits, and session management via an integrated API backend. - Offers user-friendly commands for edits, exports, credits checks, and timeline management, with seamless cloud processing. - Provides error handling, credit system, multiple export formats, and detailed workflow tips for optimal results.
Metadata
Slug image-to-video-motion-control
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 Motion Control?

convert images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 50MB. marketers, social media creators, filmmakers use... It is an AI Agent Skill for Claude Code / OpenClaw, with 77 downloads so far.

How do I install Image To Video Motion Control?

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

Is Image To Video Motion Control free?

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

Which platforms does Image To Video Motion Control support?

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

Who created Image To Video Motion Control?

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

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