Awesome-openclaw-skills cursor-agent
A comprehensive skill for using the Cursor CLI agent for various software engineering tasks (updated for 2026 features, includes tmux automation guide).
git clone https://github.com/sundial-org/awesome-openclaw-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/cursor-agent" ~/.claude/skills/sundial-org-awesome-openclaw-skills-cursor-agent && rm -rf "$T"
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/cursor-agent" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-cursor-agent && rm -rf "$T"
skills/cursor-agent/SKILL.mdCursor 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
(zsh) or~/.zshrc
(bash):~/.bashrcexport PATH="$HOME/.local/bin:$PATH" - Restart terminal or run
(orsource ~/.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) andagent
(backward compatible)cursor-agent - Verify installation:
oragent --versioncursor-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:
- 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 promptsShift+Enter
- Exit CLI (requires double-press for safety)Ctrl+D
- Review changes (pressCtrl+R
for instructions, navigate with arrow keys)i
- Cycle through previous messagesArrowUp
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
calls from subprocess/exec hang without TTYagent
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/rulesAGENTS.mdCLAUDE.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