快速判断
通过BatchEdits自动剪辑视频、添加字幕并去除静音。
适合任务
- 按 SkillHub 收录说明复用成熟任务流程。
- 通过下载包离线阅读完整 Skill 内容。
- 结合热度指标优先评估常用 Skill。
输入与输出
输入:任务目标、上下文材料、文件路径、约束条件或需要处理的内容。
输出:按 Skill 说明生成的文档、代码、检查结果、计划、建议或操作步骤。
示例任务
- 使用 Batchedits 帮我处理当前任务,并说明需要准备哪些输入。
- 根据 Batchedits 的说明,先列出使用前的安全检查项。
安装方式
- 下载本站提供的 Skill ZIP 并解压。
- 把解压后的 Skill 目录放入当前 AI 工具支持的
skills目录。 - 如需在线查看原始内容,可打开 GitHub 的
SKILL.md。
在线原始地址:skillhub-batchedits/SKILL.md
风险边界
SkillHub 提供了源站安全报告入口,但本站不替代人工审查。使用前仍需检查权限、外部依赖和敏感数据边界。
SKILL.md 文档介绍
Turn your OpenClaw into an autonomous video editor using BatchEdits. Use when you need to add captions, remove silences, or apply custom styles to videos. Covers creating styles, uploading local videos, processing, and checking video status directly from WhatsApp, Telegram, or the CLI.
Setup
1. Create an account at your BatchEdits instance.
2. Obtain your OAuth Client Token from the dashboard settings.
3. Provide your OAuth token to OpenClaw. You can do this securely by running:
openclaw config set env.BATCHEDITS_API_KEY client_xxxxx*(Alternatively, you can export BATCHEDITS_API_KEY=... in your shell, or add it to the .env file in the folder where you run OpenClaw)*
4. Connect the BatchEdits MCP Server to your OpenClaw setup by running this in your terminal:
openclaw config set mcp.servers.batchedits '{"type": "sse", "url": "https://batchedits.com/api/mcp"}'Auth
The MCP server uses your .env key automatically. Under the hood, any direct HTTP uploads authenticate using standard OAuth 2.0:
Authorization: Bearer <BATCHEDITS_API_KEY>1. Get Available Actions
Use the list_actions tool.
Returns an array of action templates (e.g., remove_silence, add_captions) with their id, name, and description. You need the id to build a style.
2. Create a Style
Use the create_style tool to build a reusable video editing preset.
Arguments:
name: e.g. "Silence Remover"actions: JSON string of templates (e.g.,[{"id": "action_123"}])
Returns the new styleId.
3. Upload Video
Use the upload_videos tool.
Arguments:
filePaths: Array of absolute paths (e.g.,["/path/to/local/video.mp4"])
Because video files are large binaries, this tool returns a ready-to-run curl command. You must execute the returned curl command in your terminal to upload the local file to the server. Parse the JSON output of the curl command to get the new videoId.
4. Process Video
Use the process_video tool to start the edit.
Arguments:
videoId: The ID from step 3styleId: The ID from step 2
5. Check Results
Use the list_videos tool.
Returns a list of your videos with their current status: pending, processing, completed, or failed.
Recommended Workflow for Video Editing
1. Identify the local video file provided by the user (e.g., downloaded from Telegram).
2. Determine the requested edits (captions, silence removal, etc.).
3. Check get_styles to see if a matching style already exists. If not, use list_actions and create_style to make one.
4. Call upload_videos to get the upload command.
5. Execute the curl upload command and extract the videoId.
6. Call process_video to start the job on the remote server.
7. Inform the user that the video is processing.
8. Call list_videos to check when the video reaches completed status.
Tips
- Always check
get_stylesfirst. Reusing existing styles is faster than creating a new one every time! - Uploading videos is handled via
curlbecause OpenClaw needs to stream large local binaries to the remote server efficiently. - You can queue multiple videos to the same style for bulk processing by repeating the upload & process steps!