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mano-cua马诺库阿

Agent Skill

mano-cua 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

33,728

周安装

1,434

GitHub Stars

3

下载量

11,816
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:mano-cua(马诺库阿)
来源仓库:https://github.com/hanningwang/mano-cua
安装命令:
openclaw skills install mano-cua
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 mano-cua

简介

基于 VLA 模型实现 GUI 自动化任务,支持屏幕视觉交互操作。

  • 适用于软件测试、表单填写与界面流程验证等场景。
  • 输入自然语言任务描述,自动识别控件并执行点击、输入等动作。
  • 需确保屏幕分辨率与元素定位稳定,避免因 UI 变动导致失败。
  • 通过 clawhub 安装,运行于 OpenClaw,依赖本地 GPU 推理环境。

SKILL.md

name
mano-cua
description
Computer use for GUI automation tasks via VLA models. Use when the user describes a task in natural language that requires visual screen interaction and no API or CLI exists for the target app.
homepage
https://github.com/Mininglamp-AI/mano-skill
metadata
{"openclaw": {"emoji": "🖥️", "install": [{"id": "brew", "kind": "brew", "formula":"Mininglamp-AI/tap/mano-cua", "bins":["mano-cua"],"label": "Install mano-cua (brew)"}]}}

mano-cua

Desktop GUI automation driven by natural language. Captures screenshots, sends them to a cloud-based hybrid vision model, and executes the returned actions on the local machine — click, type, scroll, drag, and more.

Requirements

  • A system with a graphical desktop (macOS / Windows / Linux)
  • mano-cua binary installed

Installation

macOS / Linux (Homebrew):

brew install Mininglamp-AI/tap/mano-cua

Windows:

Download the latest mano-cua-windows.zip from GitHub Releases, extract it, and add the folder to your PATH.

Usage

# Run a task (cloud mode, default)
mano-cua run "your task description"

# Run with options
mano-cua run "task" --minimize --max-steps 10

# Open a URL in the browser before starting the task
mano-cua run "task" --url "https://example.com"

# Open an app before starting the task (use the macOS app name, e.g. 'Notes', 'Safari', 'Google Chrome')
mano-cua run "task" --app "Notes"

# Run in local mode (on-device inference, macOS Apple Silicon only)
mano-cua run "task" --local

# Stop the current running task
mano-cua stop

Run mano-cua --help or mano-cua <command> --help for full flags and options.

Note: Only one task can run at a time per device. If you need to start a new task, first stop the current one with mano-cua stop.
--app vs --url: Use one or the other, not both. --app launches a desktop application by its macOS name (as shown in Spotlight search). --url opens a URL in the default browser. Both bring the target to the foreground before the agent starts.
Tip for local mode: Write task descriptions with explicit step-by-step instructions for best results. For example, instead of "search for iphone on Xiaohongshu", write "click the search box at the top, type iphone, click the search button, then click the first result". Explicit steps significantly improve local model accuracy.

Local Mode

Runs Mano-P entirely on-device via MLX. No data leaves the machine. Requires macOS with Apple Silicon (M1+).

Setup:

mano-cua check
mano-cua install-sdk
mano-cua install-model

Run:

mano-cua run "click the search box, type openai, click search, click the first result to open OpenAI homepage" --local --url "https://www.google.com"
mano-cua run "click the search box, type iphone, click the search button, open the first post" --local --url "https://www.xiaohongshu.com" --minimize --max-steps 15
mano-cua run "create a new note and type hello world" --local --app "Notes"

Examples

# Cloud mode (default — no setup needed)
mano-cua run "Open WeChat and tell FTY that the meeting is postponed"
mano-cua run "Search for AI news in Xiaohongshu and show the first post" --minimize --max-steps 20

# Cloud mode with --app or --url
mano-cua run "Create a calendar event for Friday 20:00 named Team Meeting" --app "Microsoft Outlook"
mano-cua run "Compare available plans for the AeroAPI" --url "https://www.flightaware.com/"

# Local mode — use explicit step-by-step task descriptions for best accuracy
mano-cua run "click the editor area, select all and delete, type hello world" --local --url "https://mano.mininglamp.com/md2wechat/golden.html"
mano-cua run "click the search box, type openai, click search, click the first result" --local --url "https://www.google.com" --minimize
mano-cua run "create a new note and type hello world" --local --app "Notes"

# Stop the current task (use before starting a new one)
mano-cua stop

How It Works

The current screenshot is captured and sent to the cloud at each step. A hybrid vision solution decides the next action:

  • Mano model — handles straightforward, lightweight tasks with rapid output.
  • Claude CUA model — handles complex tasks requiring deeper reasoning.

The system automatically selects the appropriate model based on task complexity.

In local mode (--local), a local Mano-P model runs on-device via MLX. No network calls for inference.

Supported Interactions

click · type · hotkey · scroll · drag · mouse move · screenshot · wait · app launch · url direction

Status Panel

A small UI panel is displayed on the top-right corner of the screen to track and manage the current session status.

Data, Privacy & Safety

  • What is sent: Screenshots of the primary display and the task description are sent to mano.mininglamp.com — these are the minimal inputs required for the vision model to determine the next action.
  • What is NOT sent: No local files, clipboard content, or system credentials are read or transmitted. All network calls are in a single module (task_model.py) for easy review.
  • Local mode: All inference runs on-device using Mano-P (model weights). No data leaves the machine.
  • Authentication: No API key or credentials are required. The client identifies itself with a locally generated device ID (~/.myapp_device_id) — no secrets are embedded in the binary.
  • Supply chain: The full client is open source. The Homebrew formula builds directly from this public source, ensuring the installed binary is fully auditable.
  • User control: Users can stop any session at any time via the UI panel or mano-cua stop.

Important Notes

  • Do not use the mouse or keyboard during the task. Manual input while mano-cua is running may cause unexpected behavior.
  • Multiple displays: only the primary display is used. All mouse movements, clicks, and screenshots are restricted to that display.

Platform Support

macOS is the preferred and most tested platform. Adaptations for Windows and Linux are not yet fully completed — minor issues are expected.

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

81.95%
按下载量换算9,683

安全审计

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可疑

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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

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