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图像处理敏感数据clawhub未标认证来源可访问clear审计通过

magic-image2video魔法图像 2 视频

Agent Skill

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

总安装

7,584

周安装

316

GitHub Stars

2

下载量

2,528
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:magic-image2video(魔法图像 2 视频)
来源仓库:https://github.com/zhangyuangao/magic-image2video
安装命令:
openclaw skills install magic-image2video
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install magic-image2video

简介

依据用户提供图文生成视频任务并提交至远程 API 处理。

  • 兼容多种图像格式输入与不同视频编码输出选项。
  • 实际生成质量取决于上游模型能力与算力资源配置。
  • 商用场景需签署服务协议明确知识产权归属。magic-image2video 属于图像处理类 Skill,可作为该场景下的辅助能力补充。
  • 网络延迟可能影响任务提交与结果返回速度。

SKILL.md

name
magic-image2video
description
Generate a video task based on user-provided text and images (supports image URLs and local file paths), and submit it to a remote video service using an API Key.
homepage
metadata
{ "openclaw": { "emoji": "🎬", "requires": { "bins": ["python"], "env":["MAGIC_API_KEY"], "primaryEnv":"MAGIC_API_KEY" } } }

Text and Image to Video Skill

Create a video generation task based on provided text content and images. The task is submitted immediately; the system will automatically poll the task status and retrieve the video link.

Usage Scenarios

Recommended for these situations:

  • "Turn this image into a video as I describe"
  • "Please help me make a video from this image according to my requirements"
  • "Use this image to generate a video as requested"
  • "Generate a video based on text and an image"

Not for These Scenarios

Do not use for the following cases:

  • The user asks for video editing, trimming, or adding special effects → Please use a video editing tool
  • The user requests screen recording or capture → Please use a screen recording tool
  • The user only wants to check the progress of an existing video task → Please guide them to check in the related file or system

Prerequisites

export MAGIC_API_KEY="your-key"

MAGIC_API_KEY is the required environment variable for the remote video service client.


Overall Workflow (Agent Guide)

  1. Extract the full text (TEXT) and image address or path (IMAGE) from the user's message.
  2. Use the video-create subcommand to create the task, read the stdout JSON output, and extract the task_id.
  3. Clearly inform the user of the task_id in the chat by outputting "Video generation task has been created, task ID: task_id. I will keep checking the task status and inform you when the video link is ready."
  4. Use the video-wait subcommand with --task-id to poll the task until completion. Task status equal to 2 means success.
  5. Extract the video_url from the video-wait command's stdout.
  6. Clearly inform the user of the final video link video_url in the chat. If timeout occurs, report it as well.

Python Client (Step-by-Step Example & Chat Output)

Step 1: Create the Video Task and Show the task_id in Chat

  1. Obtain the desired video text from the user and store it in TEXT; get the image address and store it in IMAGE.

- If the text contains double quotes ", be sure to escape them (e.g., replace " with \") to prevent command parsing errors.

  1. Run the following command (invoked by the agent tool; {baseDir} will be replaced with the skill directory):
python3 {baseDir}/scripts/media_gen_client.py video-create \
  --text  "TEXT" --image "IMAGE"
  1. Read the command's standard output (stdout), which is JSON, for example:
   {
    "biz_code": 10000,
    "msg": "Success",
    "data": {
        "task_id": "2032443088023777280"
    },
    "trace_id": "664c6e22-1edd-11f1-bf4c-8262dce7d13f"
  }
  1. Parse the task_id from the JSON (e.g. "abc-123"), and inform the user in the chat:

- Output: "Video generation task has been created, task ID: task_id. I will keep checking the task status and inform you when the video link is ready."

Step 2: Poll Task Status and Output the Final video_url in Chat

  1. Use the task_id obtained in the previous step.
  1. Execute this command (poll every 10 seconds, wait up to 600 seconds; if timeout, please try again later):
python3 {baseDir}/scripts/media_gen_client.py video-wait --task-id YOUR_TASK_ID --poll 10 --timeout 600
  1. Read the standard output. On success, the JSON output looks like:
   {
    "biz_code": 10000,
    "msg": "Success",
    "data": {
        "task_id": "1234567890",
        "task_status": 2,
        "video_url": "https://www.magiclight.com/examplevideo.mp4"
    },
    "trace_id": "c89aeca8-1edd-11f1-bf4c-8262dce7d13f"
}
  1. Parse the key fields from the output:
  • Task status (e.g., task_status: 2), where status 2 means success
  • Video link (e.g., video_url: "https://example.com/path/to/video.mp4")
  1. Recommended chat reply flow:
  • Summarize the key info in plain language, for example:

> "Task complete ✅ > task_id: abc-123 > Video link: https://example.com/path/to/video.mp4"

  1. If the result shows task failure or timeout (e.g., success is false, video_url is empty, or error is timeout):
  • Explain the failure reason (include error info if possible), and inform the user they can retry later or check possible issues like input or quota.

Script Output Requirements

  • The agent must always:

- Parse stdout JSON. - Clearly inform the user of both the task ID and video link in the chat.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.51%
按下载量换算1,934

安全审计

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通过

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通过

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权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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