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mhogan2013-9

Image To Video Google

by mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install image-to-video-google
Description
Skip the learning curve of professional editing software. Describe what you want — turn these photos into a short video with transitions and music — and get...
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 three landscape photos from a recent trip into a 1080p MP4"
  • "turn these photos into a short video with transitions and music"
  • "converting still photos into shareable videos for marketers"

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 Google — Convert Images Into Shareable Videos

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 three landscape photos from a recent trip, type "turn these photos into a short video with transitions and music", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer than 10 images keeps processing time under a minute.

Matching Input to Actions

User prompts referencing image to video google, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: image-to-video-google
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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

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

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.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a short video with transitions and music" — 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.

Common Workflows

Quick edit: Upload → "turn these photos into a short video with transitions and music" → 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 claims (upload images, request a render, return a download URL), but review these points before installing: (1) Privacy — your images will be uploaded to mega-api-prod.nemovideo.ai; do not send sensitive photos unless you trust that service and its retention policy. (2) Credential use — the skill will use NEMO_TOKEN from your environment if present or acquire an anonymous token automatically; supplying your own token gives the skill access tied to that token. (3) Naming mismatch and metadata inconsistency — the 'Google' name vs. nemovideo.ai endpoints and the differing configPath declarations are red flags about quality control; ask the publisher to clarify. (4) Attribution headers — the skill reads its frontmatter and may inspect install paths to build headers; confirm this behavior is acceptable. If you need higher assurance, request the skill author to provide a privacy policy, a canonical homepage, or to remove the misleading branding and fix metadata inconsistencies.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-google Version: 1.0.0 The skill bundle provides instructions for an AI agent to interface with the nemovideo.ai API to convert images into videos. It handles session management, anonymous token acquisition, and asynchronous rendering workflows. While the instructions direct the agent to check its installation path (e.g., ~/.clawhub/) to set platform attribution headers, this behavior is documented and serves the stated purpose of the skill. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.
Capability Assessment
Purpose & Capability
The skill name/description (image-to-video) matches the API calls and endpoints in SKILL.md (upload, render, export). However the name includes 'Google' while all endpoints are for nemovideo.ai (branding mismatch), and the SKILL.md metadata lists a required config path (~/.config/nemovideo/) even though the registry metadata earlier reported no required config paths — an internal inconsistency.
Instruction Scope
Runtime instructions explicitly upload user images and send them to a remote GPU-backed render service (mega-api-prod.nemovideo.ai). That is expected for this purpose, but you should be aware that user files are transmitted off-device. The skill also instructs the agent to read this file's YAML frontmatter and to detect the install path (~/.clawhub/, ~/.cursor/skills/) to set attribution headers — this implies the agent will inspect the skill's own files and possibly local install paths.
Install Mechanism
Instruction-only skill with no install spec and no code files. Nothing is downloaded or written to disk by an installer; risk from install mechanism is low.
Credentials
Only one credential is requested (NEMO_TOKEN), which is proportionate for an API-backed render service. The skill will use NEMO_TOKEN if present, otherwise it instructs generating an anonymous token via the service's auth endpoint. The SKILL.md metadata also references a config path (~/.config/nemovideo/), which wasn't listed in the registry's 'Required config paths' — this mismatch should be resolved before trusting the skill.
Persistence & Privilege
always:false and no special privileges requested. The skill can be invoked autonomously (platform default), but it does not request permanent 'always' inclusion or system-wide configuration changes.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-google
  3. After installation, invoke the skill by name or use /image-to-video-google
  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 Google — easily turn photos into AI-generated shareable videos. - Upload JPG, PNG, WEBP, or HEIC images (up to 200MB) and describe the video you want. - Automatically connects to a cloud API: no software installation required. - Supports requests for video exports, credits/balance, uploading images, and live status updates. - Exports videos with transitions, music, and text overlays; returns 1080p MP4s (and more formats). - Shows progress/status during rendering; provides actionable feedback for errors (file size, credits, etc.). - Designed for marketers and users who want quick, professional video creation without technical complexity.
Metadata
Slug image-to-video-google
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 Google?

Skip the learning curve of professional editing software. Describe what you want — turn these photos into a short video with transitions and music — and get... It is an AI Agent Skill for Claude Code / OpenClaw, with 117 downloads so far.

How do I install Image To Video Google?

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

Is Image To Video Google free?

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

Which platforms does Image To Video Google support?

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

Who created Image To Video Google?

It is built and maintained by mhogan2013-9 (@mhogan2013-9); the current version is v1.0.0.

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