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peand-rover

Image To Video Like Grok

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

Getting Started

Share your images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my images"
  • "export 1080p MP4"
  • "animate this image into a short"

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 Like Grok — Turn Images Into Video Clips

This tool takes your images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a single product photo or landscape image and want to animate this image into a short video clip like Grok does — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: high-contrast images with clear subjects produce the smoothest motion results.

Matching Input to Actions

User prompts referencing image to video like grok, 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-like-grok
  • 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 JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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 → "animate this image into a short video clip like Grok does" → 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 into a short video clip like Grok does" — 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 what it says: it sends your images to an external rendering service (mega-api-prod.nemovideo.ai) and requires or will obtain a NEMO_TOKEN to run jobs. Before installing or invoking it, consider: (1) Privacy — your images and any metadata will be uploaded to nemovideo.ai; avoid sending sensitive or private images unless you trust the service and its retention policy. (2) Token behavior — if NEMO_TOKEN is not present the skill will call the service to create an anonymous token (100 free credits, 7-day expiry) and use it; decide whether you prefer to provide your own token. (3) Filesystem access — the skill may inspect install paths / frontmatter for attribution headers; if you want to limit file reads, check agent permissions. (4) Verify the service/domain if you have security concerns (confirm nemovideo.ai is the intended provider). If you want greater assurance, ask the skill author for a privacy/retention policy and explicit confirmation of exactly what data is uploaded and how tokens are stored.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-like-grok Version: 1.0.0 The skill is a legitimate integration for an AI video generation service (nemovideo.ai). It provides instructions for the agent to manage authentication via an anonymous token flow, handle multipart file uploads, and poll a cloud rendering pipeline for MP4 generation. The behavior is strictly aligned with the stated purpose of 'Image to Video' conversion, and there are no indicators of data exfiltration, malicious command execution, or unauthorized access to sensitive local files beyond its own configuration directory.
Capability Assessment
Purpose & Capability
The declared purpose (convert images to short videos via a cloud pipeline) matches the required env var (NEMO_TOKEN) and the API endpoints and workflows described. One minor inconsistency: the top-level registry metadata listed no required config paths, but the skill's frontmatter metadata includes a configPaths entry (~/.config/nemovideo/). This appears to be a metadata mismatch rather than a functional mismatch with the stated purpose.
Instruction Scope
Instructions stay within the conversion/rendering domain (auth, session creation, upload, SSE, export polling). They explicitly instruct the agent to look for NEMO_TOKEN, call the anonymous-token endpoint if absent, maintain a session_id, and include attribution headers. The skill also instructs detecting install path and reading the skill frontmatter for version (filesystem reads) to populate X-Skill-Platform/X-Skill-Version headers — this filesystem probing is for attribution and not essential to the core conversion task, so it is noteworthy but not necessarily malicious.
Install Mechanism
No install spec and no code files — instruction-only skill. This is the lowest-risk install profile; nothing is written to disk by an installer or downloaded during installation.
Credentials
Only a single credential (NEMO_TOKEN) is declared as required/primary, which is proportional to a cloud API client. The skill will also attempt to obtain an anonymous token via the nemovideo.ai auth endpoint if NEMO_TOKEN is not present — that behavior is reasonable but should be understood (it creates a short-lived anonymous token on your behalf). There are no unrelated credentials requested.
Persistence & Privilege
always is false, there is no install-time persistence or requests to modify other skills or global settings. The skill keeps session state during an active conversation (session_id) as required for the workflow; this is scoped to runtime and not permanent system privilege.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-like-grok
  3. After installation, invoke the skill by name or use /image-to-video-like-grok
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Animate still images into video clips using AI with simple, text-based controls. - Upload product or landscape photos and generate 1080p MP4 video clips in 30–60 seconds. - Hassle-free interface: no manual timeline editing or export settings required. - Automatic cloud backend setup; handles user authentication and session management transparently. - Supports direct user prompts for export, balance, status, and upload actions. - Robust error handling with clear feedback for common issues and quota limits. - Multiple video, image, and audio formats supported for exports.
Metadata
Slug image-to-video-like-grok
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 Like Grok?

Turn a single product photo or landscape image into 1080p animated video clips just by typing what you need. Whether it's turning still images into short ani... It is an AI Agent Skill for Claude Code / OpenClaw, with 56 downloads so far.

How do I install Image To Video Like Grok?

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

Is Image To Video Like Grok free?

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

Which platforms does Image To Video Like Grok support?

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

Who created Image To Video Like Grok?

It is built and maintained by peandrover adam (@peand-rover); the current version is v1.0.0.

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