agent-desktop Skill Install & Guide
io.clawhub.lahfir/agent-desktop · v0.1.32
Reliable computer use via native OS accessibility trees. Use when an AI agent needs to see and operate desktop applications (click buttons, fill forms, navigate menus, read UI state, toggle checkboxes, scroll, drag, type text, take screenshots, manage windows, use clipboard, manage notifications). Covers 59 command names (55 operational; four held-input names fail closed until daemon ownership exists) across observation, interaction, keyboard/mouse, app lifecycle, notifications (macOS), clipboard, wait, session lifecycle, and a `skills` command that bundles docs straight from the binary. Triggers on: "click button", "fill form", "open app", "read UI", "computer use", "operate desktop", "accessibility tree", "snapshot app", "type into field", "navigate menu", "toggle checkbox", "take screenshot", "desktop automation", "agent-desktop", or any desktop GUI interaction task. Supports the macOS Phase 1 adapter, with Windows and Linux planned against the same core contracts.
Copy the install config on this page first, then verify docs and permissions upstream.
Popularity
Overview
Reliable computer use via native OS accessibility trees. Use when an AI agent needs to see and operate desktop applications (click buttons, fill forms, navigate menus, read UI state, toggle checkboxes, scroll, drag, type text, take screenshots, manage windows, use clipboard, manage notifications). Covers 59 command names (55 operational; four held-input names fail closed until daemon ownership exists) across observation, interaction, keyboard/mouse, app lifecycle, notifications (macOS), clipboard, wait, session lifecycle, and a `skills` command that bundles docs straight from the binary. Triggers on: "click button", "fill form", "open app", "read UI", "computer use", "operate desktop", "accessibility tree", "snapshot app", "type into field", "navigate menu", "toggle checkbox", "take screenshot", "desktop automation", "agent-desktop", or any desktop GUI interaction task. Supports the macOS Phase 1 adapter, with Windows and Linux planned against the same core contracts. agent-desktop is a Agent Skill listed from ClawHub. This page includes an overview, setup tutorial, install commands, and use cases for Trae, Tongyi Lingma, Cursor, Claude Code, and VS Code.
Use cases
AgentHub Verified AvailabilityTested & Ready
Automated pipeline validated install commands, protocol & client compatibility
Send this prompt to your AI to install the Skill
RecommendedFollow the install guide at https://myagenthub.cn/install/skill.md?lang=en to automatically detect the current IDE and install the skill "lahfir/agent-desktop" without asking, and tell me how to verify it afterwards.
💡Paste into your AI coding assistant (Cursor, Trae, Claude Code) — the agent will handle download and configuration automatically.
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Choose install method
# 改 --ai 切换客户端:trae | lingma | workbuddy | kimi | qwen | cursor | claude-code | windsurf | cline | vscode | codex | openclaw
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai cursor -ySetup tutorial
- Open the agent-desktop page and confirm the source is ClawHub.
- Copy the install command for Trae, Lingma, Cursor, Claude Code, or universal CLI.
- Run it, or place SKILL.md under .trae/skills/, .lingma/skills/, or .cursor/skills/.
- Reload the client, then describe your task so the agent can match this skill.
Install commands
Install commands and setup steps are in the HTML so search engines and no-JS browsers can read them without running client JavaScript.
Universal — Skills CLI (recommended)
AgentHub CLI (change --ai)
# 改 --ai 切换客户端:trae | lingma | workbuddy | kimi | qwen | cursor | claude-code | windsurf | cline | vscode | codex | openclaw
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai cursor -yOne-click API download
# 手动下载(Cursor 项目级示例)
mkdir -p .cursor/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .cursor/skills/agent-desktopCursor
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai cursor -yOne-click API download
mkdir -p .cursor/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .cursor/skills/agent-desktopClawHub CLI, then copy
# 在项目根目录执行 install
clawhub install lahfir/agent-desktop
mkdir -p .cursor/skills/agent-desktop
cp -R ./skills/agent-desktop/. .cursor/skills/agent-desktop/
# 源:./skills/agent-desktop/SKILL.md
# 目标:.cursor/skills/agent-desktop/SKILL.mdTrae (ByteDance)
- Trae natively supports Skill specs: project-level in .trae/skills/<name>/, global in ~/.trae/skills/
- Copy and run the command in your project terminal to download SKILL.md
- Reload Trae window, then describe your task in AI chat to activate automatically
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai trae -yOne-click API download
mkdir -p .trae/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .trae/skills/agent-desktopUser directory
mkdir -p ~/.trae/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.trae/skills/agent-desktopTongyi Lingma (Alibaba)
- Tongyi Lingma supports skills in project .lingma/skills/<name>/ or global ~/.lingma/skills/
- Run the command to install SKILL.md
- In Lingma Agent mode, prompt your task and the skill will be automatically loaded
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai lingma -yOne-click API download
mkdir -p .lingma/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .lingma/skills/agent-desktopUser directory
mkdir -p ~/.lingma/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.lingma/skills/agent-desktopWorkBuddy / CodeBuddy (Tencent)
- WorkBuddy reads skills only from .workbuddy/skills/<name>/ (user-level ~/.workbuddy/skills/); .codebuddy/skills/ belongs to CodeBuddy
- The Skills CLI command installs with -a codebuddy and appends a copy step into .workbuddy/skills
- AgentHub CLI (--ai workbuddy) syncs it for you; reload the chat panel so the skill gets indexed
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai workbuddy -yOne-click API download
mkdir -p .workbuddy/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .workbuddy/skills/agent-desktopUser directory
mkdir -p ~/.workbuddy/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.workbuddy/skills/agent-desktopClaude Code
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai claude-code --global -yOne-click API download
mkdir -p ~/.claude/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.claude/skills/agent-desktopClawHub CLI, then copy
clawhub install lahfir/agent-desktop
mkdir -p ~/.claude/skills/agent-desktop
cp -R ./skills/agent-desktop/. ~/.claude/skills/agent-desktop/
# 源:./skills/agent-desktop/SKILL.md
# 目标:~/.claude/skills/agent-desktop/SKILL.md
# https://clawhub.ai/lahfir/agent-desktopKimi Code (Moonshot AI)
- Kimi Code supports standard Agent Skills: project-level in .agents/skills/<name>/, global in ~/.agents/skills/
- Run the command to install
- In Kimi Code CLI, describe your task to trigger the skill
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai kimi -yOne-click API download
mkdir -p .agents/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .agents/skills/agent-desktopUser directory
mkdir -p ~/.agents/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.agents/skills/agent-desktopQwen Code (Alibaba)
- Qwen Code supports project .qwen/skills/<name>/ and global ~/.qwen/skills/
- Run the command to deploy SKILL.md
- Prompt the agent to trigger the skill
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai qwen -yOne-click API download
mkdir -p .qwen/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .qwen/skills/agent-desktopUser directory
mkdir -p ~/.qwen/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.qwen/skills/agent-desktopWindsurf
- Windsurf supports project-level .windsurf/skills/<name>/ or global ~/.codeium/windsurf/skills/
- Run the install command and refresh Cascade
- Cascade will auto-activate the skill based on its description
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai windsurf -yOne-click API download
mkdir -p .windsurf/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .windsurf/skills/agent-desktopUser directory
mkdir -p ~/.codeium/windsurf/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.codeium/windsurf/skills/agent-desktopCline
- Cline supports standard .agents/skills/<name>/ structure
- Run the command to install the skill
- Ask questions in the Cline panel to trigger the skill
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai cline -yOne-click API download
mkdir -p .agents/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d .agents/skills/agent-desktopCherry Studio
- Use this skill as an Assistant system prompt in Cherry Studio
- Copy the command to view SKILL.md text
- Paste the contents into Cherry Studio Assistant system prompt
# 下载并提取 SKILL.md 指令内容
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -p /tmp/agent-desktop.zip SKILL.md
# 复制上述输出,粘贴至 Cherry Studio → 助手设置 →「系统提示词」VS Code / GitHub Copilot
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai vscode -yOne-click API download
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
mkdir -p .github/skills/agent-desktop
unzip -o /tmp/agent-desktop.zip -d .github/skills/agent-desktopOpenAI Codex
AgentHub CLI (change --ai)
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init lahfir/agent-desktop --ai codex --global -yOne-click API download
mkdir -p ~/.codex/skills/agent-desktop
curl -sL "https://clawhub.ai/api/v1/download?slug=agent-desktop&version=0.1.32" -o /tmp/agent-desktop.zip
unzip -o /tmp/agent-desktop.zip -d ~/.codex/skills/agent-desktopClawHub CLI, then copy
clawhub install lahfir/agent-desktop
mkdir -p ~/.codex/skills/agent-desktop
cp -R ./skills/agent-desktop/. ~/.codex/skills/agent-desktop/
# 源:./skills/agent-desktop/SKILL.md
# 目标:~/.codex/skills/agent-desktop/SKILL.mdOpenClaw — ClawHub CLI
# OpenClaw / ClawHub CLI(推荐)
# 在项目根或 OpenClaw 工作区目录执行
clawhub install lahfir/agent-desktop
# 安装后 SKILL.md 位于:
# ./skills/agent-desktop/SKILL.md
# (若已配置 OpenClaw 工作区,则在 <workspace>/skills/agent-desktop/)
# 仅查看不安装
clawhub inspect lahfir/agent-desktopTroubleshooting & Common ErrorsFAQ
Common connection errors and verified fixes for agent-desktop
Getting 'connection closed' or exit code 1 in Cursor / Claude Code for agent-desktop?
Usually caused by missing runtime paths or IDE environment inheritance. Fix steps: 1. Verify Node.js 18+ (npx) or Python 3.10+ (uvx) is installed; 2. Run 'which npx' or 'which uvx' in terminal, and replace 'command' with absolute path; 3. Reload or restart the client window after modifying config.
# Check binary path in terminal: which npx node -v
Getting 'spawn npx ENOENT' or 'command not found'?
The editor background process does not inherit your full terminal PATH. Solution: Globally install the package, or set the absolute binary path (e.g. C:\Program Files\nodejs\npx.cmd on Windows, or /usr/local/bin/npx on macOS).
Tool calls timing out or failing to download packages?
First-time package downloading might be slow or timeout due to network limits. Configure a reliable mirror or check outbound proxy settings.
Agent does not match or apply agent-desktop during conversations?
Verify SKILL.md is located at .cursor/skills/agent-desktop/SKILL.md (Cursor) or ~/.claude/skills/agent-desktop/SKILL.md (Claude Code). You can explicitly mention the skill name in your prompt to boost match confidence.
Tool Mock Playground
Sandboxagent-desktop Rule Injection & Agent Behavior Simulation · Preview tool schema & outputs without local runtime
{
"skill": "agent-desktop",
"rulePath": ".cursor/skills/agent-desktop/SKILL.md",
"userGoal": "请使用 agent-desktop 的方法与标准帮我完成当前任务",
"client": "Cursor / Claude Code"
}Click 'Run Mock' above
to preview the raw response returned to the LLM
Decision Guide: Why & When to Use
Assess suitability before installing to save trial-and-error time
- E2E testing
- Headless screenshots
- Form automation
- Bulk fetch when a stable REST API exists
- CAPTCHA bypass (compliance risk)
Playwright MCP + Filesystem MCP → AI writes tests and runs browser actions
Skill hands-on: install to visible results
Follow the full lab (expected UI/output + contrast checks). After installing this item, verify with the tutorial prompts.
An Agent Skill is a folder with SKILL.md instructions. After install, the AI loads it automatically when your task matches its description.
How to use
After installing, describe your task in chat (or mention the skill name). The agent reads the skill description to decide when to activate it, then follows the instructions in SKILL.md. Check loaded skills via /skills in Claude Code or in your client settings.
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Unified Manifest
{
"id": "io.clawhub.lahfir/agent-desktop",
"type": "skill",
"version": "0.1.32",
"displayName": "agent-desktop",
"description": "Reliable computer use via native OS accessibility trees. Use when an AI agent needs to see and operate desktop applications (click buttons, fill forms, navigate menus, read UI state, toggle checkboxes, scroll, drag, type text, take screenshots, manage windows, use clipboard, manage notifications). Covers 59 command names (55 operational; four held-input names fail closed until daemon ownership exists) across observation, interaction, keyboard/mouse, app lifecycle, notifications (macOS), clipboard, wait, session lifecycle, and a `skills` command that bundles docs straight from the binary. Triggers on: \"click button\", \"fill form\", \"open app\", \"read UI\", \"computer use\", \"operate desktop\", \"accessibility tree\", \"snapshot app\", \"type into field\", \"navigate menu\", \"toggle checkbox\", \"take screenshot\", \"desktop automation\", \"agent-desktop\", or any desktop GUI interaction task. Supports the macOS Phase 1 adapter, with Windows and Linux planned against the same core contracts.",
"author": {
"name": "lahfir",
"url": "https://clawhub.ai/lahfir"
},
"homepage": "https://clawhub.ai/lahfir/agent-desktop",
"distribution": {
"packages": [
{
"registryType": "source",
"identifier": "lahfir/agent-desktop",
"version": "0.1.32",
"runtimeHint": "clawhub install"
}
],
"remotes": []
},
"dependencies": [],
"installTargets": [
"openclaw",
"claude-code",
"claude-desktop",
"cursor",
"codex",
"vscode"
],
"keywords": [
"downloads:3366",
"stars:0",
"installs:52",
"Accessibility",
"CLI",
"Desktop Automation",
"Gui Automation"
],
"provenance": {
"origin": "clawhub",
"originalId": "lahfir/agent-desktop",
"originalUrl": "https://clawhub.ai/lahfir/agent-desktop",
"isOfficial": false,
"status": "active"
}
}