# Agent Browser

> Use this skill to extract page state and automate web interactions with the agent-browser CLI (navigate, snapshot, click, fill, screenshot). Use this when you need deterministic browser automation or scraping via ref-based elements.

- Skill: `majiayu000/agent-browser-34` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/agent-browser-34`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/agent-browser-34/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/agent-browser-34

---


# agent-browser: CLI Browser Automation

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

## Philosophy

- Prefer accessibility-first selectors (refs) for stability.
- Re-snapshot after navigation or DOM changes.
- Keep actions minimal and observable.

## When to use

- You need to interact with live web pages or forms.
- You need screenshots or PDFs of UI states.
- You need to scrape data with deterministic steps.

## Inputs

- Target URL(s).
- Desired interactions (click/fill/scroll).
- Output artifacts (screenshots, PDFs, extracted text).

## Outputs

- Action results and snapshots.
- Saved artifacts (png/pdf) when requested.
- Extracted content for further processing.

## Constraints / Safety

- Redact secrets, tokens, and private URLs in logs.
- Avoid interacting with sensitive accounts without explicit approval.
- Do not run destructive actions on production systems.

## Variation

- Use refs for deterministic steps; use semantic locators when refs are unstable.
- Use `--session` for parallel flows when isolation is required.
- Prefer JSON snapshots for parsing and automation.

## Anti-Patterns

- Clicking without a fresh snapshot after navigation.
- Using brittle selectors when refs are available.
- Running long sequences without verification checkpoints.

## Validation

- Confirm each step with a snapshot or expected UI change.
- Fail fast: stop at the first failed step and fix before continuing.
- See `references/contract.yaml` (schema_version: 1) and `references/evals.yaml`.

## Remember

The agent is capable of extraordinary work in this domain. These guidelines unlock that potential—they don't constrain it.
Use judgment, adapt to context, and push boundaries when appropriate.

## Setup Check

```bash
# Check installation
command -v agent-browser >/dev/null 2>&1 && echo "Installed" || echo "NOT INSTALLED - run: npm install -g agent-browser && agent-browser install"
```

### 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 --json

# 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
```

### 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 screenshot --full output.png    # Full page 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
```

## 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 (Parallel Browsers)

```bash
# Run multiple independent browser sessions
agent-browser --session browser1 open https://site1.com
agent-browser --session browser2 open https://site2.com

# List active sessions
agent-browser session list
```

## Examples

### Login Flow

```bash
agent-browser open https://app.example.com/login
agent-browser snapshot -i
# Output shows: 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 --json
# Parse JSON to find story links
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 button
agent-browser screenshot confirmation.png
```

### 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
```

## JSON Output

Add `--json` for structured output:

```bash
agent-browser snapshot -i --json
```

Returns:
```json
{
  "success": true,
  "data": {
    "refs": {
      "e1": {"name": "Submit", "role": "button"},
      "e2": {"name": "Email", "role": "textbox"}
    },
    "snapshot": "- button \"Submit\" [ref=e1]\n- textbox \"Email\" [ref=e2]"
  }
}
```

## vs Playwright MCP

| Feature | agent-browser (CLI) | Playwright MCP |
|---------|---------------------|----------------|
| Interface | Bash commands | MCP tools |
| Selection | Refs (@e1) | Refs (e1) |
| Output | Text/JSON | Tool responses |
| Parallel | Sessions | Tabs |
| Best for | Quick automation | Tool 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