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vcarolxhberger

Image To Video Gemini

by vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install image-to-video-gemini
Description
Turn a single product photo or landscape image into 1080p animated video clips just by typing what you need. Whether it's converting static images into short...
README (SKILL.md)

Getting Started

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

Try saying:

  • "convert a single product photo or landscape image into a 1080p MP4"
  • "turn this image into a 5-second animated video clip"
  • "converting static images into short AI-generated video clips for content creators, marketers, social media managers"

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 https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

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.

Image to Video Gemini — Convert Images into Video Clips

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

A quick example: upload a single product photo or landscape image, type "turn this image into a 5-second animated video clip", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: high-contrast images with clear subjects produce the most natural-looking motion.

Matching Input to Actions

User prompts referencing image to video gemini, 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 requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-gemini, 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).

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this image into a 5-second animated video clip" — concrete instructions get better results.

Max file size is 20MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

PNG images with clean backgrounds give Gemini the clearest subject to animate.

Common Workflows

Quick edit: Upload → "turn this image into a 5-second animated video clip" → 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.

Usage Guidance
This skill appears to do what it says: remote image→video rendering using a single service token. Before installing, consider: (1) Do you trust the external domain (mega-api-prod.nemovideo.ai)? Network requests will send image files and session tokens to that service. (2) If you do not set NEMO_TOKEN, the skill will automatically request an anonymous token from the provider — decide whether you want the agent to obtain and possibly store that token. (3) The skill mentions a config path (~/.config/nemovideo/) in its frontmatter even though the registry said none; ask the author whether tokens/sessions are persisted to disk and where. (4) If privacy is a concern, avoid providing sensitive images or set a per-session token rather than a long-lived environment variable. If you need higher assurance, request the skill author to clarify the config-path behavior and provide a privacy/terms link for the backend service.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-gemini Version: 1.0.0 The skill is a legitimate integration for an image-to-video generation service hosted at mega-api-prod.nemovideo.ai. It implements standard API patterns for authentication, session management, file uploads, and Server-Sent Events (SSE) for processing. The instructions in SKILL.md are well-structured and include security-conscious directives, such as advising the agent not to expose tokens or raw API output to the user. While it performs minor environment fingerprinting to identify the host platform (e.g., Cursor or ClawHub), there is no evidence of malicious intent, data exfiltration, or unauthorized execution.
Capability Assessment
Purpose & Capability
The skill claims to convert images to short videos using a remote GPU backend and requires a single NEMO_TOKEN credential — this is coherent with its stated purpose. The skill's declared need for a token and session management matches a cloud-rendering workflow.
Instruction Scope
SKILL.md is instruction-only and confines actions to creating sessions, uploading images, sending SSE messages, polling render status, and returning download URLs. These actions match the image→video purpose. It does instruct the agent to (a) look for NEMO_TOKEN in the environment and otherwise obtain an anonymous token by calling the remote auth endpoint, and (b) detect install path to set X-Skill-Platform — both are expected but do require filesystem and network access. There are no instructions to read unrelated environment variables or arbitrary local files beyond the images you upload.
Install Mechanism
No install spec or code files — this is instruction-only, which minimizes disk-write risk. The skill relies on network calls to a third-party API (mega-api-prod.nemovideo.ai) but does not download or install additional packages.
Credentials
Only NEMO_TOKEN is declared as required and that aligns with the API usage. The SKILL.md also documents automatic anonymous-token acquisition when the env var is absent (POST to the provider's auth endpoint). The frontmatter also references a config path (~/.config/nemovideo/) which could imply writing/storing tokens or session state; this conflicts with the registry's earlier 'no required config paths' entry and should be clarified.
Persistence & Privilege
The skill is not marked always:true and does not request elevated system privileges. It can run autonomously (the platform default) and will communicate with an external service, but it does not attempt to modify other skills or system-wide configs in its instructions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-gemini
  3. After installation, invoke the skill by name or use /image-to-video-gemini
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Image to Video Gemini 1.0.0 — First release. - Instantly convert a single product photo or landscape image into a 1080p animated video clip via a cloud backend. - Setup is fully automated: anonymous, token-based sign-in with 100 free credits (7-day expiry). - Upload still images and describe your desired video; get a rendered MP4 in 30–90 seconds (no manual timeline editing needed). - All operations (upload, generate, export, check credits) handled by simple prompts or file uploads. - Supports various formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac. - Clean error handling and session state tracking keep you updated throughout the process.
Metadata
Slug image-to-video-gemini
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 Gemini?

Turn a single product photo or landscape image into 1080p animated video clips just by typing what you need. Whether it's converting static images into short... It is an AI Agent Skill for Claude Code / OpenClaw, with 65 downloads so far.

How do I install Image To Video Gemini?

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

Is Image To Video Gemini free?

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

Which platforms does Image To Video Gemini support?

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

Who created Image To Video Gemini?

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

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