安装方式
手动下载安装
下载 ZIP 后解压到技能目录即可安装。若在桌面客户端 WebView中直接下载出现异常,本站会改为提示页 + 原始链接,请按页内说明操作。
下载 ZIP (shub-cursor-agent-v2.1.0.zip)触发指令
/cursor-agent
跨平台安装指引
该技能声明兼容以下 1 个平台,将 ZIP 解压到对应目录即可被识别。
unzip shub-cursor-agent-v2.1.0.zip -d ~/.claude/skills/
mkdir -p 创建;启用 Skill 后请重启对应 Agent 让配置生效。
使用指南
Cursor Agent
围绕 Cursor Agent:在 Cursor IDE 中驱动 Agent 完成编码、重构与多文件编辑;快捷键与模型设置以客户端为准。 无需在每次任务前把零散英文说明手工拼进上下文,也 减少 与客户端默认行为脱节的试错;具体命令、钩子与 JSON 参数仍以 ZIP 包内 SKILL.md 为权威。下文结构与站内 MCP CLI 类专题稿相同:何时用、前置、流程、速查与故障。
何时使用
- 在 Cursor IDE 中驱动 Agent 完成编码、重构与多文件编辑
- 快捷键与模型设置以客户端为准
- 已获取本技能 ZIP,并准备在 Claude Code / OpenClaw 中按 SKILL.md 挂载。
- 希望用中文专题稿快速判断「该不该启用」,再深入英文 SKILL 查参数与边界。
- 需要与团队对齐同一套触发方式、目录约定或回调格式时。
前置条件
- 通用:可运行 Claude Code 或文档要求的客户端;有可读写的项目工作区(或 SKILL.md 指定的沙箱目录)。
- 权威细节:API Key / OAuth、钩子路径、环境变量以 ZIP 内 SKILL.md 为准。
典型流程
- 从 ClawHub / 站内分发获取技能 ZIP,校验版本与校验和(若提供)。
- 阅读 SKILL.md 的安装段落:目录落点、客户端类型(Claude Code / OpenClaw / 脚本)。
- 用文档中的最小示例完成第一次调用(单文件修改、单次查询或单次委派)。
- 确认工作目录、权限边界与输出路径后,再处理多文件或长耗时任务。
- 需要回调 / Webhook / 通知时,按 SKILL.md 配置端点并在测试环境先验通。
与 ZIP / SKILL.md 的关系
站内专题稿与 MCP CLI 类 oss 稿同样:概括何时用、怎么接、怎么排错;命令模板、钩子名、JSON 字段、版本矩阵一律以 ZIP 内 SKILL.md 与 ClawHub 上游为准。
命令示例(摘自包内 SKILL.md)
以下为从上游 SKILL.md(或入库正文)自动抽取的终端/脚本片段;路径、环境变量与参数以当前 ZIP 与官方说明为准。
ClawHub slug:cursor-agent(安装命令以 SKILL.md / claw CLI 为准)。
curl https://cursor.com/install -fsS | bash
brew install --cask cursor-cli
agent login
export CURSOR_API_KEY=your_api_key_here
agent update
# or
agent upgrade
agent
agent "Add error handling to this API"
agent models
# or
agent --list-models
agent --model gpt-5
agent -p 'Run tests and report coverage'
# or
agent --print 'Refactor this file to use async/await'
站内入库时的触发命令(完整语义见 ZIP):
# 使用本技能时可在对话中引用或执行上述指令;完整参数与示例见下载包内 SKILL.md。
/cursor-agent
最佳实践
- 先 SKILL.md 再猜参数;站内专题稿不替代 schema 与必填字段说明。
- 委派任务时写清验收标准(命令、文件路径、测试命令),减少来回追问。
- 长任务用文档推荐的回调 / 日志落盘代替高频轮询,省 Token 也省机器负载。
- 多技能同时启用时,注意钩子加载顺序与重复工具调用(以 SKILL.md 冲突说明为准)。
调试与排错
- 打开 stderr 与客户端日志;PTY/tmux 场景同时看面板最后几十行输出。
- 参数错误时对照 SKILL.md 中的 JSON/CLI 示例(引号、转义、工作目录)。
- 网络类失败:查代理、防火墙、MCP 传输方式(stdio / HTTP / SSE)。
速查
| 动作 | 说明 |
|------|------|
| 获取技能包 | ClawHub / 站内 ZIP,核对版本 |
| 权威步骤 | 优先阅读 ZIP 内 SKILL.md |
| 首次试跑 | 使用 SKILL.md 最小示例 |
| 验收 | 对照路径、测试命令或回调负载 |
常见故障
- 无输出或立即退出 → 工作目录错误、依赖未装、或 Claude Code 未登录;按 SKILL.md 自检清单执行。
- 权限被拒绝 → 检查沙箱路径、
--permission-mode与工具白名单。 - 与简介不符 → 以英文 SKILL 与上游仓库为准,站内稿仅作结构化导读。
# 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)
```bash
curl https://cursor.com/install -fsS | bash
```
### Homebrew (macOS only)
```bash
brew install --cask cursor-cli
```
### Post-Installation Setup
**macOS:**
- Add to PATH in `~/.zshrc` (zsh) or `~/.bashrc` (bash):
```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:
```bash
agent login
```
Or use API key:
```bash
export CURSOR_API_KEY=your_api_key_here
```
## Update
Keep your CLI up to date:
```bash
agent update
# or
agent upgrade
```
## Commands
### Interactive Mode
Start an interactive session with the agent:
```bash
agent
```
Start with an initial prompt:
```bash
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:
```bash
agent models
# or
agent --list-models
```
Use a specific model:
```bash
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:
```bash
agent -p 'Run tests and report coverage'
# or
agent --print 'Refactor this file to use async/await'
```
**Output formats:**
```bash
# 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):**
```bash
agent -p 'Fix all linting errors' --force
```
**Media support:**
```bash
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**
```bash
# 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:**
```bash
# ❌ 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:
```bash
agent -p 'Review the changes in the current branch against main. Focus on security and performance.'
```
### Refactoring
Refactor code for better readability or performance:
```bash
agent -p 'Refactor src/utils.ts to reduce complexity and improve type safety.'
```
### Debugging
Analyze logs or error messages to find the root cause:
```bash
agent -p 'Analyze the following error log and suggest a fix: [paste log here]'
```
### Git Integration
Automate git operations with context awareness:
```bash
agent -p 'Generate a commit message for the staged changes adhering to conventional commits.'
```
### Batch Processing (CI/CD)
Run automated checks in CI pipelines:
```bash
# 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:
```bash
agent
# Then in interactive mode:
@src/api/
@src/models/
Review the API implementation for consistency with our data models
```