cursor-agent
Original:🇺🇸 English
Translated
A comprehensive skill for using the Cursor CLI agent for various software engineering tasks (updated for 2026 features, includes tmux automation guide).
13installs
Added on
NPX Install
npx skill4agent add aaaaqwq/claude-code-skills cursor-agentTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →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 | bashHomebrew (macOS only)
bash
brew install --cask cursor-cliPost-Installation Setup
macOS:
- Add to PATH in (zsh) or
~/.zshrc(bash):~/.bashrcbashexport PATH="$HOME/.local/bin:$PATH" - Restart terminal or run (or
source ~/.zshrc)~/.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: (primary) and
agent(backward compatible)cursor-agent - Verify installation: or
agent --versioncursor-agent --version
Authentication
Authenticate via browser:
bash
agent loginOr use API key:
bash
export CURSOR_API_KEY=your_api_key_hereUpdate
Keep your CLI up to date:
bash
agent update
# or
agent upgradeCommands
Interactive Mode
Start an interactive session with the agent:
bash
agentStart with an initial prompt:
bash
agent "Add error handling to this API"Backward compatibility: still works but is now the primary command.
cursor-agentagentModel Switching
List all available models:
bash
agent models
# or
agent --list-modelsUse a specific model:
bash
agent --model gpt-5Switch models during a session:
/modelsSession 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:
- - Switch between AI models interactively
/models - - Summarize conversation and free up context window
/compress - - Create and edit rules directly from CLI
/rules - - Create and modify custom commands
/commands - - Enable an MCP server
/mcp enable [server-name] - - Disable an MCP server
/mcp disable [server-name]
Keyboard Shortcuts
- - Add newlines for multi-line prompts
Shift+Enter - - Exit CLI (requires double-press for safety)
Ctrl+D - - Review changes (press
Ctrl+Rfor instructions, navigate with arrow keys)i - - Cycle through previous messages
ArrowUp
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-outputForce mode (auto-apply changes without confirmation):
bash
agent -p 'Fix all linting errors' --forceMedia 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 calls from subprocess/exec hang without TTY
agent
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 CursorRules & Configuration
The agent automatically loads rules from:
.cursor/rulesAGENTS.mdCLAUDE.md
Use command to create and edit rules directly from the CLI.
/rulesMCP Integration
MCP servers are automatically loaded from configuration.
mcp.jsonEnable/disable servers on the fly:
/mcp enable server-name
/mcp disable server-nameNote: 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 textMulti-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