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cursor-agentCursor Agent 搜索

Agent Skill

cursor-agent 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

367,091

周安装

15,144

GitHub Stars

17

下载量

119,940
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:cursor-agent(Cursor Agent 搜索)
来源仓库:https://github.com/swiftlysingh/cursor-agent
安装命令:
openclaw skills install cursor-agent
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 cursor-agent

简介

使用 Cursor CLI 代理执行各种软件工程任务的综合技能(更新了 2026 年功能,包括 tmux 自动化指南)。

SKILL.md

name
cursor-agent
version
2.1.0
description
A comprehensive skill for using the Cursor CLI agent for various software engineering tasks (updated for 2026 features, includes tmux automation guide).
author
Pushpinder Pal Singh

Cursor CLI Agent Skill

This skill provides a comprehensive guide and set of workflows for utilizing the Cursor CLI tool, including all features from the January 2026 update.

Installation

Standard Installation (macOS, Linux, Windows WSL)

curl https://cursor.com/install -fsS | bash

Homebrew (macOS only)

brew install --cask cursor-cli

Post-Installation Setup

macOS:

  • Add to PATH in ~/.zshrc (zsh) or ~/.bashrc (bash):
  export PATH="$HOME/.local/bin:$PATH"
  • Restart terminal or run source ~/.zshrc (or ~/.bashrc)
  • Requires macOS 10.15 or later
  • Works on both Intel and Apple Silicon Macs

Linux/Ubuntu:

  • Restart your terminal or source your shell config
  • Verify with agent --version

Both platforms:

  • Commands: agent (primary) and cursor-agent (backward compatible)
  • Verify installation: agent --version or cursor-agent --version

Authentication

Authenticate via browser:

agent login

Or use API key:

export CURSOR_API_KEY=your_api_key_here

Update

Keep your CLI up to date:

agent update
# or
agent upgrade

Commands

Interactive Mode

Start an interactive session with the agent:

agent

Start with an initial prompt:

agent "Add error handling to this API"

Backward compatibility: cursor-agent still works but agent is now the primary command.

Model Switching

List all available models:

agent models
# or
agent --list-models

Use a specific model:

agent --model gpt-5

Switch models during a session:

/models

Session Management

Manage your agent sessions:

  • List sessions: agent ls
  • Resume most recent: agent resume
  • Resume specific session: agent --resume="[chat-id]"

Context Selection

Include specific files or folders in the conversation:

@filename.ts
@src/components/

Slash Commands

Available during interactive sessions:

  • /models - Switch between AI models interactively
  • /compress - Summarize conversation and free up context window
  • /rules - Create and edit rules directly from CLI
  • /commands - Create and modify custom commands
  • /mcp enable [server-name] - Enable an MCP server
  • /mcp disable [server-name] - Disable an MCP server

Keyboard Shortcuts

  • Shift+Enter - Add newlines for multi-line prompts
  • Ctrl+D - Exit CLI (requires double-press for safety)
  • Ctrl+R - Review changes (press i for instructions, navigate with arrow keys)
  • ArrowUp - Cycle through previous messages

Non-interactive / CI Mode

Run the agent in a non-interactive mode, suitable for CI/CD pipelines:

agent -p 'Run tests and report coverage'
# or
agent --print 'Refactor this file to use async/await'

Output formats:

# Plain text (default)
agent -p 'Analyze code' --output-format text

# Structured JSON
agent -p 'Find bugs' --output-format json

# Real-time streaming JSON
agent -p 'Run tests' --output-format stream-json --stream-partial-output

Force mode (auto-apply changes without confirmation):

agent -p 'Fix all linting errors' --force

Media support:

agent -p 'Analyze this screenshot: screenshot.png'

⚠️ Using with AI Agents / Automation (tmux required)

CRITICAL: When running Cursor CLI from automated environments (AI agents, scripts, subprocess calls), the CLI requires a real TTY. Direct execution will hang indefinitely.

The Solution: Use tmux

# 1. Install tmux if not available
sudo apt install tmux  # Ubuntu/Debian
brew install tmux      # macOS

# 2. Create a tmux session
tmux kill-session -t cursor 2>/dev/null || true
tmux new-session -d -s cursor

# 3. Navigate to project
tmux send-keys -t cursor "cd /path/to/project" Enter
sleep 1

# 4. Run Cursor agent
tmux send-keys -t cursor "agent 'Your task here'" Enter

# 5. Handle workspace trust prompt (first run)
sleep 3
tmux send-keys -t cursor "a"  # Trust workspace

# 6. Wait for completion
sleep 60  # Adjust based on task complexity

# 7. Capture output
tmux capture-pane -t cursor -p -S -100

# 8. Verify results
ls -la /path/to/project/

Why this works:

  • tmux provides a persistent pseudo-terminal (PTY)
  • Cursor's TUI requires interactive terminal capabilities
  • Direct agent calls from subprocess/exec hang without TTY

What does NOT work:

# ❌ These will hang indefinitely:
agent "task"                    # No TTY
agent -p "task"                 # No TTY  
subprocess.run(["agent", ...])  # No TTY
script -c "agent ..." /dev/null # May crash Cursor

Rules & Configuration

The agent automatically loads rules from:

  • .cursor/rules
  • AGENTS.md
  • CLAUDE.md

Use /rules command to create and edit rules directly from the CLI.

MCP Integration

MCP servers are automatically loaded from mcp.json configuration.

Enable/disable servers on the fly:

/mcp enable server-name
/mcp disable server-name

Note: Server names with spaces are fully supported.

Workflows

Code Review

Perform a code review on the current changes or a specific branch:

agent -p 'Review the changes in the current branch against main. Focus on security and performance.'

Refactoring

Refactor code for better readability or performance:

agent -p 'Refactor src/utils.ts to reduce complexity and improve type safety.'

Debugging

Analyze logs or error messages to find the root cause:

agent -p 'Analyze the following error log and suggest a fix: [paste log here]'

Git Integration

Automate git operations with context awareness:

agent -p 'Generate a commit message for the staged changes adhering to conventional commits.'

Batch Processing (CI/CD)

Run automated checks in CI pipelines:

# Set API key in CI environment
export CURSOR_API_KEY=$CURSOR_API_KEY

# Run security audit with JSON output
agent -p 'Audit this codebase for security vulnerabilities' --output-format json --force

# Generate test coverage report
agent -p 'Run tests and generate coverage report' --output-format text

Multi-file Analysis

Use context selection to analyze multiple files:

agent
# Then in interactive mode:
@src/api/
@src/models/
Review the API implementation for consistency with our data models

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

83.6%
按下载量换算100,270

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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