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Image To Generator

作者 linmillsd7 · 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-generator
功能描述
generate still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for generati...
使用说明 (SKILL.md)

Getting Started

Got still images to work with? Send it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

  • "generate three product photos in JPG format into a 1080p MP4"
  • "turn these images into a short video with smooth transitions and background music"
  • "generating videos from static images for social media posts for social media creators"

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 Generator — Turn Images Into Video Clips

Send me your still 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 product photos in JPG format, type "turn these images into a short video with smooth transitions and background music", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer than five images speeds up rendering noticeably.

Matching Input to Actions

User prompts referencing image to generator, 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-generator
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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)

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the 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 → "turn these images into a short video with smooth transitions and background 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these images into a short video with smooth transitions and background 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 across platforms.

安全使用建议
This appears to be an instruction-only cloud video generator rather than local code. Before installing, be comfortable with sending selected media to mega-api-prod.nemovideo.ai, using or creating a NEMO_TOKEN, and possibly consuming service credits during rendering/export.
功能分析
Type: OpenClaw Skill Name: image-to-generator Version: 1.0.0 The skill is a standard API wrapper for the 'nemovideo.ai' image-to-video generation service. It contains instructions for the AI agent to manage sessions, handle file uploads, and poll for rendering status via the 'https://mega-api-prod.nemovideo.ai' endpoint. The logic for token acquisition and attribution headers is consistent with its stated purpose, and there is no evidence of data exfiltration, unauthorized command execution, or malicious prompt injection in SKILL.md.
能力评估
Purpose & Capability
The described capability matches the instructions: user-selected images are uploaded to a cloud backend for video rendering and export.
Instruction Scope
The skill instructs the agent to create sessions, upload files, call SSE/edit/export endpoints, and translate backend GUI-like responses into API actions. This is purpose-aligned, but users should understand the agent may perform multiple cloud API steps during a request.
Install Mechanism
There is no install spec and no code files, which limits local execution risk. However, the registry lists the source as unknown and no homepage is provided, so provider provenance is not independently established in the artifacts.
Credentials
Use of a NEMO_TOKEN and calls to a remote video service are proportionate for this cloud-rendering purpose, and the main endpoint is disclosed.
Persistence & Privilege
The artifacts describe short-lived anonymous tokens, session IDs, polling, and remote render jobs. No local persistence or background worker is shown, but remote jobs may continue if the session is interrupted.
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-generator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-generator 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 Generator — Turn Images Into Video Clips". - Upload JPG, PNG, WEBP, or HEIC images (up to 200MB) and generate 1080p MP4 video clips with smooth transitions and optional background music. - No installation needed; all processing is cloud-based and handled via remote GPUs with a typical turnaround of 30–60 seconds per video. - Automatic connection and session setup with anonymous tokens for new users; 100 free credits included. - Supports social media creators with simple workflows: upload, instruct, and download. - Includes robust error handling, session and credit management, and GUI-like interaction mapping.
元数据
Slug image-to-generator
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 Generator 是什么?

generate still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for generati... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 58 次。

如何安装 Image To Generator?

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

Image To Generator 是免费的吗?

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

Image To Generator 支持哪些平台?

Image To Generator 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 Generator?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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