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'

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