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tk8544-b

Image To Video Ai Prompt

by tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install image-to-video-ai-prompt
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 5-second"

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 AI Prompt — Convert 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 5-second cinematic video with a slow zoom effect — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: high-contrast images with clear subjects produce smoother, more accurate motion.

Matching Input to Actions

User prompts referencing image to video ai prompt, 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.

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

  • X-Skill-Source: image-to-video-ai-prompt
  • 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.

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.

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.

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

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)

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 "animate this image into a 5-second cinematic video with a slow zoom effect" — 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 across social platforms and presentations.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second cinematic video with a slow zoom effect" → 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 does what it says (uploads images and asks a cloud service to render videos), but note: (1) images and any associated metadata will be sent to https://mega-api-prod.nemovideo.ai — do not upload sensitive images unless you trust that service; (2) if you don't provide NEMO_TOKEN, the skill will automatically create an anonymous token by POSTing to the provider, which may create an account/credits on your behalf — review that behavior before allowing it; (3) the SKILL.md metadata mentions a config path (~/.config/nemovideo/) even though the registry listing stated no required config path — this inconsistency should be clarified by the publisher; (4) there is no homepage or clear publisher information — verify the domain, service legitimacy, and privacy terms before use. Recommended actions: provide your own NEMO_TOKEN only if you trust the service, avoid uploading sensitive content, ask the publisher to clarify the configPath mismatch and to publish a homepage/owner verification, and consider running the skill in a limited or sandboxed environment first.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-ai-prompt Version: 1.0.0 The skill is a functional integration for the NemoVideo AI service (mega-api-prod.nemovideo.ai), allowing users to convert images to videos. It provides clear instructions for the agent to manage authentication via the NEMO_TOKEN, handle session states, and interact with specific API endpoints for uploading and rendering. While it includes logic for environment fingerprinting (detecting the installation path to set attribution headers), this behavior is transparently documented for telemetry purposes and lacks any indicators of malicious intent, data exfiltration, or unauthorized execution.
Capability Assessment
Purpose & Capability
Name and description match the runtime instructions: the skill uploads images to a cloud rendering backend and returns rendered video. The single required credential (NEMO_TOKEN) is coherent with contacting a third‑party API for rendering.
Instruction Scope
The SKILL.md stays within the stated purpose: it describes session creation, SSE message flows, uploads, and export polling against the nemovideo.ai API. It instructs reading NEMO_TOKEN from the environment and, if missing, obtaining an anonymous token via an HTTP POST. It also instructs reading this file's YAML frontmatter and detecting install path to set attribution headers. These file/path reads and automatic anonymous-token generation are reasonable for operation but expand the skill's runtime scope and have privacy implications (uploads go to an external service).
Install Mechanism
Instruction-only skill with no install spec or code files — nothing is written to disk by an installer. Lowest install risk.
Credentials
Declared primaryEnv is NEMO_TOKEN which matches usage. However, the SKILL.md frontmatter metadata lists a configPath (~/.config/nemovideo/) while the registry summary said 'Required config paths: none' — this is an inconsistency. Also the skill will automatically POST to an anonymous-token endpoint to create a token if NEMO_TOKEN is absent; that behavior creates credentials on your behalf and causes images and metadata to be sent to a third party. For users expecting local-only processing or strict control over tokens, this is potentially problematic.
Persistence & Privilege
The skill is not always-enabled and does not request persistent system-wide privileges. It asks to detect an install path and to read its own YAML frontmatter, which is limited in scope and acceptable for attribution purposes. It does not modify other skills or system config per the provided instructions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-ai-prompt
  3. After installation, invoke the skill by name or use /image-to-video-ai-prompt
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the Image to Video AI Prompt skill. - Instantly converts single images into 1080p animated video clips based on text prompts. - Automated cloud-based backend setup with free anonymous token generation and session handling. - Supports seamless file upload, video export, and prompt-driven editing with no manual timeline or export steps. - Handles common actions via prompts (upload, credits, export, status) with clear user feedback and error handling. - Exports in major video and image formats; optimized for product, landscape, and quick social content.
Metadata
Slug image-to-video-ai-prompt
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 Ai Prompt?

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 74 downloads so far.

How do I install Image To Video Ai Prompt?

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

Is Image To Video Ai Prompt free?

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

Which platforms does Image To Video Ai Prompt support?

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

Who created Image To Video Ai Prompt?

It is built and maintained by tk8544-b (@tk8544-b); the current version is v1.0.0.

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