AgentSkillsCN

agent-browser

利用 Vercel 的 agent-browser CLI 实现浏览器自动化。当用户说“浏览网站”“填写表单”“截取屏幕截图”“测试网页”时,可运用此技能。该技能采用基于引用的元素选择方式。

SKILL.md
--- frontmatter
name: agent-browser
description: Browser automation using Vercel's agent-browser CLI. This skill should be used when the user says "browse a website", "fill a form", "take a screenshot", or "test a web page". Uses ref-based element selection.
user-invocable: true

agent-browser: CLI Browser Automation

Vercel's headless browser CLI designed for AI agents. Uses ref-based selection (@e1, @e2) from accessibility snapshots.

Setup Check

bash
command -v agent-browser >/dev/null 2>&1 && echo "Installed" || echo "NOT INSTALLED"

Install if needed

bash
npm install -g agent-browser
agent-browser install  # Downloads Chromium

Core Workflow

The snapshot + ref pattern is optimal for LLMs:

  1. Navigate to URL
  2. Snapshot to get interactive elements with refs
  3. Interact using refs (@e1, @e2, etc.)
  4. Re-snapshot after navigation or DOM changes
bash
# Step 1: Open URL
agent-browser open https://example.com

# Step 2: Get interactive elements with refs
agent-browser snapshot -i

# Step 3: Interact using refs
agent-browser click @e1
agent-browser fill @e2 "search query"

# Step 4: Re-snapshot after changes
agent-browser snapshot -i

Key Commands

Navigation

bash
agent-browser open <url>       # Navigate to URL
agent-browser back             # Go back
agent-browser forward          # Go forward
agent-browser reload           # Reload page
agent-browser close            # Close browser

Snapshots (Essential for AI)

bash
agent-browser snapshot              # Full accessibility tree
agent-browser snapshot -i           # Interactive elements only (recommended)
agent-browser snapshot -i --json    # JSON output for parsing
agent-browser snapshot -c           # Compact (remove empty elements)
agent-browser snapshot -d 3         # Limit depth
agent-browser snapshot -s @e5       # Scope to element subtree

Interactions

bash
agent-browser click @e1                    # Click element
agent-browser dblclick @e1                 # Double-click
agent-browser fill @e1 "text"              # Clear and fill input
agent-browser type @e1 "text"              # Type without clearing
agent-browser press Enter                  # Press key
agent-browser hover @e1                    # Hover element
agent-browser check @e1                    # Check checkbox
agent-browser uncheck @e1                  # Uncheck checkbox
agent-browser select @e1 "option"          # Select dropdown option
agent-browser scroll down 500              # Scroll (up/down/left/right)
agent-browser scrollintoview @e1           # Scroll element into view

Get Information

bash
agent-browser get text @e1          # Get element text
agent-browser get html @e1          # Get element HTML
agent-browser get value @e1         # Get input value
agent-browser get attr href @e1     # Get attribute
agent-browser get title             # Get page title
agent-browser get url               # Get current URL
agent-browser get count "button"    # Count matching elements

Screenshots & PDFs

bash
agent-browser screenshot                      # Viewport screenshot
agent-browser screenshot --full               # Full page
agent-browser screenshot output.png           # Save to file
agent-browser pdf output.pdf                  # Save as PDF

Wait

bash
agent-browser wait @e1              # Wait for element
agent-browser wait 2000             # Wait milliseconds
agent-browser wait "text"           # Wait for text to appear
agent-browser wait --url "pattern"  # Wait for URL match

Semantic Locators (Alternative to Refs)

bash
agent-browser find role button click --name "Submit"
agent-browser find text "Sign up" click
agent-browser find label "Email" fill "user@example.com"
agent-browser find placeholder "Search..." fill "query"

Sessions & Profiles

Sessions (Parallel Isolated Browsers)

bash
agent-browser --session browser1 open https://site1.com
agent-browser --session browser2 open https://site2.com
agent-browser session list

Profiles (Persistent State Across Restarts)

bash
# Profiles preserve cookies, localStorage, login sessions
agent-browser --profile ~/.myapp-profile open https://app.example.com

Authentication

Skip UI Login with Headers

bash
agent-browser open https://api.example.com --headers '{"Authorization": "Bearer <token>"}'

Save/Load Auth State

bash
# After logging in via UI
agent-browser state save auth-state.json

# Reuse in future sessions
agent-browser state load auth-state.json
agent-browser open https://app.example.com  # Already logged in

Debug Mode

bash
# Run with visible browser window
agent-browser --headed open https://example.com
agent-browser --headed snapshot -i
agent-browser --headed click @e1

Examples

Login Flow

bash
agent-browser open https://app.example.com/login
agent-browser snapshot -i
# Output: textbox "Email" [ref=e1], textbox "Password" [ref=e2], button "Sign in" [ref=e3]
agent-browser fill @e1 "user@example.com"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait 2000
agent-browser snapshot -i  # Verify logged in

Search and Extract

bash
agent-browser open https://news.ycombinator.com
agent-browser snapshot -i
agent-browser get text @e12  # Get headline text
agent-browser click @e12     # Click to open story

Form Filling

bash
agent-browser open https://forms.example.com
agent-browser snapshot -i
agent-browser fill @e1 "John Doe"
agent-browser fill @e2 "john@example.com"
agent-browser select @e3 "United States"
agent-browser check @e4  # Agree to terms
agent-browser click @e5  # Submit
agent-browser screenshot confirmation.png

JSON Output

bash
agent-browser snapshot -i --json

Returns structured data with refs for programmatic parsing.

vs Playwright MCP

Featureagent-browser (CLI)Playwright MCP
InterfaceBash commandsMCP tools
SelectionRefs (@e1)Refs (e1)
OutputText/JSONTool responses
ParallelSessionsTabs
Best forQuick automationTool integration

Use agent-browser when:

  • You prefer Bash-based workflows
  • You want simpler CLI commands
  • You need quick one-off automation

Use Playwright MCP when:

  • You need deep MCP tool integration
  • You want tool-based responses
  • You're building complex automation