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agent-browser-automation▌

aradotso/trending-skills · updated Apr 8, 2026

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$npx skills add https://github.com/aradotso/trending-skills --skill agent-browser-automation
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summary

Skill by ara.so — Daily 2026 Skills collection.

skill.md

agent-browser

Skill by ara.so — Daily 2026 Skills collection.

agent-browser is a headless browser automation CLI built in Rust, designed for AI agents. It wraps Chrome via the Chrome DevTools Protocol (CDP) and exposes a fast, ergonomic command-line interface for navigation, interaction, accessibility snapshots, screenshots, network interception, and more — with no Node.js or Playwright runtime required.

Installation

Recommended (npm global)

npm install -g agent-browser
agent-browser install  # Download Chrome for Testing (first time only)

macOS (Homebrew)

brew install agent-browser
agent-browser install

Rust / Cargo

cargo install agent-browser
agent-browser install

Local project dependency

npm install agent-browser
# Add to package.json scripts or invoke via npx

Linux (with system dependencies)

agent-browser install --with-deps

Quick Start

agent-browser open https://example.com
agent-browser snapshot                        # Accessibility tree with @refs (best for AI)
agent-browser click @e2                       # Click by ref from snapshot
agent-browser fill @e3 "[email protected]"   # Fill by ref
agent-browser get text @e1                    # Get text content
agent-browser screenshot page.png
agent-browser close

Core Commands

Navigation

agent-browser open <url>           # Navigate (aliases: goto, navigate)
agent-browser get url              # Get current URL
agent-browser get title            # Get page title
agent-browser close                # Close browser (aliases: quit, exit)

Accessibility Snapshot (recommended for AI agents)

agent-browser snapshot             # Returns accessibility tree with @ref IDs
agent-browser snapshot -i          # Interactive / compact mode

Snapshot output includes @eN refs you can use directly:

@e1 [button] "Submit"
@e2 [textbox] "Email" value=""
@e3 [link] "Sign in"

Then act on them:

agent-browser fill @e2 "[email protected]"
agent-browser click @e1

Interaction

agent-browser click <sel>                     # Click element
agent-browser dblclick <sel>                  # Double-click
agent-browser fill <sel> <text>               # Clear and fill input
agent-browser type <sel> <text>               # Type into element
agent-browser press <key>                     # Press key (Enter, Tab, Control+a)
agent-browser keyboard type <text>            # Type at current focus (real keystrokes)
agent-browser keyboard inserttext <text>      # Insert text without key events
agent-browser hover <sel>                     # Hover element
agent-browser select <sel> <value>            # Select dropdown option
agent-browser check <sel>                     # Check checkbox
agent-browser uncheck <sel>                   # Uncheck checkbox
agent-browser scroll down 500                 # Scroll (up/down/left/right, optional px)
agent-browser scroll down --selector "#feed"  # Scroll within element
agent-browser scrollintoview <sel>            # Scroll element into view
agent-browser drag <src> <target>             # Drag and drop
agent-browser upload <sel> /path/file.pdf     # Upload file

Screenshots & PDF

agent-browser screenshot                          # Save to temp dir, print path
agent-browser screenshot page.png                 # Save to path
agent-browser screenshot --full page.png          # Full-page screenshot
agent-browser screenshot --annotate               # Numbered element labels overlay
agent-browser screenshot --screenshot-dir ./shots # Custom output directory
agent-browser screenshot --screenshot-format jpeg --screenshot-quality 80
agent-browser pdf output.pdf                      # Save page as PDF

Getting Element Info

agent-browser get text <sel>           # Text content
agent-browser get html <sel>           # innerHTML
agent-browser get value <sel>          # Input value
agent-browser get attr <sel> <attr>    # Attribute value
agent-browser get count <sel>          # Count matching elements
agent-browser get box <sel>            # Bounding box
agent-browser get styles <sel>         # Computed styles
agent-browser get cdp-url              # CDP WebSocket URL

State Checks

agent-browser is visible <sel>
agent-browser is enabled <sel>
agent-browser is checked <sel>

Semantic Locators (find)

agent-browser find role button click --name "Submit"
agent-browser find text "Sign In" click
agent-browser find label "Email" fill "[email protected]"
agent-browser find placeholder "Search..." fill "rust"
agent-browser find testid "login-btn" click
agent-browser find first ".item" click
agent-browser find nth 2 "a" text
agent-browser find role textbox fill "hello" --name "Username"

Actions: click, fill, type, hover, focus, check, uncheck, text

Waiting

agent-browser wait "#modal"                          # Wait for element visible
agent-browser wait 2000                              # Wait N milliseconds
agent-browser wait --text "Welcome back"             # Wait for text
agent-browser wait --url "**/dashboard"              # Wait for URL pattern
agent-browser wait --load networkidle                # Wait for load state
agent-browser wait --fn "window.appReady === true"   # Wait for JS condition
agent-browser wait "#spinner" --state hidden         # Wait for element to disappear

Load states: load, domcontentloaded, networkidle

JavaScript Eval

agent-browser eval "document.title"
agent-browser eval "JSON.stringify(window.__STATE__)"
agent-browser eval -b "BASE64_ENCODED_JS"
echo "return document.body.innerHTML" | agent-browser eval --stdin

Batch Execution (efficient multi-step)

echo '[
  ["open", "https://example.com"],
  ["snapshot", "-i"],
  ["fill", "@e2", "[email protected]"],
  ["click", "@e1"],
  ["screenshot", "result.png"]
]' | agent-browser batch --json

# Stop on first failure
agent-browser batch --bail < commands.json

Tabs & Frames

agent-browser tab                    # List tabs
agent-browser tab new https://...    # New tab with URL
agent-browser tab 2                  # Switch to tab 2
agent-browser tab close              # Close current tab
agent-browser frame "#my-iframe"     # Switch into iframe
agent-browser frame main             # Return to main frame

Cookies & Storage

agent-browser cookies
agent-browser cookies set session_id "abc123"
agent-browser cookies clear

agent-browser storage local
agent-browser storage local set theme dark
agent-browser storage local clear
agent-browser storage session set cart '{"items":[]}'

Network

agent-browser network route "**/api/users" --body '{"users":[]}'  # Mock response
agent-browser network route "**/ads/**" --abort                    # Block requests
agent-browser network unroute                                       # Remove all routes
agent-browser network requests --filter api                        # View requests
agent-browser network har start
agent-browser network har stop recording.har

Browser Settings

agent-browser set viewport 1280 800
agent-browser set viewport 375 812 2        # With device pixel ratio (retina)
agent-browser set device "iPhone 14"
agent-browser set geo 37.7749 -122.4194
agent-browser set offline on
agent-browser set headers '{"X-Custom":"value"}'
agent-browser set credentials admin secret
agent-browser set media dark

Auth State

agent-browser state save ./auth.json    # Save cookies + localStorage
agent-browser state load ./auth.json    # Restore auth state
agent-browser state list                # List saved states
agent-browser state show auth.json      # Summary of saved state

Dialogs

agent-browser dialog accept             # Accept alert/confirm/prompt
agent-browser dialog accept "My input"  # Accept prompt with text
agent-browser dialog dismiss

Clipboard

agent-browser clipboard read
agent-browser clipboard write "Hello, World!"
agent-browser
how to use agent-browser-automation

How to use agent-browser-automation on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add agent-browser-automation
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aradotso/trending-skills --skill agent-browser-automation

The skills CLI fetches agent-browser-automation from GitHub repository aradotso/trending-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/agent-browser-automation

Reload or restart Cursor to activate agent-browser-automation. Access the skill through slash commands (e.g., /agent-browser-automation) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client
  • ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • ›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • ⚠Not validating competitive research—verify facts before sharing
  • ⚠Accepting user stories without involving engineering team
  • ⚠Over-relying on frameworks without qualitative judgment
  • ⚠Not customizing outputs to company culture and communication style
  • ⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • −Don't publish competitive analysis without fact-checking
  • −Don't finalize user stories without engineering review
  • −Don't make prioritization decisions solely on AI scoring
  • −Don't skip customer validation of generated requirements
  • −Don't ignore company-specific context and culture

💡 Pro Tips

  • ★Provide context: company goals, constraints, customer feedback
  • ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • ★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.5★★★★★28 reviews
  • ★★★★★Soo Bansal· Dec 16, 2024

    We added agent-browser-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Hana Haddad· Nov 7, 2024

    agent-browser-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Aarav Mehta· Oct 26, 2024

    agent-browser-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • ★★★★★Xiao Sharma· Sep 5, 2024

    agent-browser-automation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Yash Thakker· Sep 1, 2024

    Keeps context tight: agent-browser-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Arya Rahman· Sep 1, 2024

    Registry listing for agent-browser-automation matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Sophia Diallo· Aug 24, 2024

    Solid pick for teams standardizing on skills: agent-browser-automation is focused, and the summary matches what you get after install.

  • ★★★★★Dhruvi Jain· Aug 20, 2024

    I recommend agent-browser-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • ★★★★★Henry Menon· Aug 20, 2024

    Useful defaults in agent-browser-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Mia Lopez· Jul 15, 2024

    I recommend agent-browser-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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