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Image To Video Models

作者 susan4731-wilfordf · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install image-to-video-models
功能描述
Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 50MB), say something like "an...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "convert a single product photo or landscape image into a 1080p MP4"
  • "animate this image into a 5-second video with smooth motion"
  • "turning static images into short animated video clips for marketers, social media creators, designers"

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 Models — Convert Images into Video Clips

Drop your still images in the chat and tell me what you need. I'll handle the AI video generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a single product photo or landscape image, ask for animate this image into a 5-second video with smooth motion, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — high-contrast images with clear subjects produce the most natural-looking motion.

Matching Input to Actions

User prompts referencing image to video models, 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.

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

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

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

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 Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s 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 video with smooth motion" — concrete instructions get better results.

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

Use PNG for images with transparency to preserve edge quality before conversion.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video with smooth motion" → Download MP4. Takes 30-90 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.

安全使用建议
This skill appears to do what it says: it uploads images and uses a third‑party rendering API that requires a NEMO_TOKEN. Before installing, confirm you trust the service (source/homepage is missing in the registry), because your images (and any metadata) will be sent to mega-api-prod.nemovideo.ai. Ask the publisher: who runs the backend, what is the data retention/usage policy, and why does the frontmatter reference ~/.config/nemovideo/ when the instructions don't explain using it? If you proceed, prefer using an anonymous or disposable token/account for testing, avoid sending sensitive images, and verify where tokens are stored and how long they remain valid.
功能分析
Type: OpenClaw Skill Name: image-to-video-models Version: 1.0.0 The skill bundle provides a functional integration for an image-to-video conversion service hosted at `mega-api-prod.nemovideo.ai`. It contains detailed instructions for the AI agent to handle authentication via `NEMO_TOKEN`, manage cloud-based processing sessions, and interpret Server-Sent Events (SSE) for real-time updates. The behavior is strictly aligned with the stated purpose, and the instructions include security-conscious directives such as protecting tokens from exposure and handling errors gracefully.
能力评估
Purpose & Capability
The skill is an instruction-only connector to a cloud video-rendering backend (mega-api-prod.nemovideo.ai). Requesting a single API token (NEMO_TOKEN) and uploading images to render videos is coherent with the stated purpose.
Instruction Scope
Runtime instructions confine actions to authenticating (or obtaining an anonymous token), creating a session, uploading images, using SSE for edits, and polling for export—all appropriate for a cloud render workflow. The skill requires attaching three attribution headers and auto-detecting an install path for X-Skill-Platform; that platform-detection requirement may be awkward for an instruction-only skill (no install path present) and could require the agent to inspect its environment. The SKILL.md also lists a config path (~/.config/nemovideo/) in its frontmatter, but the rest of the instructions never explain reading or writing that path (metadata vs. instructions mismatch).
Install Mechanism
No install spec or code files are present; this is instruction-only. Nothing is being downloaded or written by an installer—lowest install risk.
Credentials
Only one credential is required (NEMO_TOKEN / primaryEnv), which matches the described API usage. The skill additionally documents how to obtain an anonymous token if none is present. However, the frontmatter's claimed config path (~/.config/nemovideo/) is not justified in the instructions and should be clarified (why would a config file be needed?).
Persistence & Privilege
always:false and user-invocable:true (defaults) — the skill does not request forced/global inclusion. It keeps a session_id for job management (expected). It does not instruct modifying other skills or system-wide settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install image-to-video-models
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-models 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of "Image to Video Models" skill — convert still images (JPG, PNG, WEBP, HEIC) into animated video clips using cloud-based AI. - Supports seamless upload, AI-guided animation from text instructions, and 1080p MP4 exports. - Simple onboarding: automatic cloud token setup and user feedback ("Connecting...", "Ready!"). - Built for fast workflows — no manual animation skills needed, ideal for marketers, social creators, and designers. - Provides credit tracking, status monitoring, error handling, and tips for best results. - Session-based editing enables iterative video creation and batch processing.
元数据
Slug image-to-video-models
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Image To Video Models 是什么?

Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 50MB), say something like "an... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 95 次。

如何安装 Image To Video Models?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install image-to-video-models」即可一键安装,无需额外配置。

Image To Video Models 是免费的吗?

是的,Image To Video Models 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Image To Video Models 支持哪些平台?

Image To Video Models 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Image To Video Models?

由 susan4731-wilfordf(@susan4731-wilfordf)开发并维护,当前版本 v1.0.0。

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