agent-browser

casper-studios/casper-marketplace · updated Apr 8, 2026

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$npx skills add https://github.com/casper-studios/casper-marketplace --skill agent-browser
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summary

Browser automation and end-to-end testing using Vercel's agent-browser CLI. Uses ref-based element targeting for reliable, AI-friendly browser interaction.

skill.md

Agent Browser Testing Skill

Browser automation and end-to-end testing using Vercel's agent-browser CLI. Uses ref-based element targeting for reliable, AI-friendly browser interaction.

Quick Decision Tree

What do you need?
├─ Take a screenshot of a page?
│  └─ agent-browser open [url] && agent-browser screenshot
├─ Fill out a form?
│  └─ open → snapshot -i → fill @ref → click @submit → snapshot
├─ Test a login flow?
│  └─ See references/authentication.md
├─ Run an E2E test?
│  └─ See references/testing-patterns.md
├─ Scrape page content?
│  └─ agent-browser open [url] && agent-browser snapshot -i
└─ Debug element targeting?
   └─ agent-browser snapshot -i --format json

Installation

# Install agent-browser globally
npm install -g agent-browser

# Install browser dependencies (Chromium)
agent-browser install

# Verify installation
agent-browser --version

Core Concept: Ref-Based Targeting

Agent-browser uses refs (like @e1, @e2, @e3) to identify interactive elements on the page. These refs are assigned when you take a snapshot.

# Take a snapshot with interactive elements labeled
agent-browser snapshot -i

# Output shows refs:
# @e1: [button] "Sign In"
# @e2: [input] Email field
# @e3: [input] Password field
# @e4: [button] "Submit"

# Use refs to interact
agent-browser click @e1
agent-browser fill @e2 "[email protected]"

Important: Refs are session-specific and invalidate when the page changes. Always re-snapshot after navigation or DOM updates.

Essential Workflow

# 1. Open the target URL
agent-browser open https://example.com

# 2. Take a snapshot to see the page and get refs
agent-browser snapshot -i

# 3. Interact with elements using refs
agent-browser click @e1
agent-browser fill @e2 "test value"

# 4. Take another snapshot to verify changes
agent-browser snapshot -i

Common Commands Quick Reference

Navigation

agent-browser open <url>              # Navigate to URL
agent-browser back                    # Go back
agent-browser forward                 # Go forward
agent-browser refresh                 # Reload page

Snapshots

agent-browser snapshot                # Text snapshot
agent-browser snapshot -i             # With interactive refs
agent-browser snapshot --format json  # JSON output
agent-browser screenshot [path]       # Save screenshot

Interaction

agent-browser click @ref              # Click element
agent-browser fill @ref "value"       # Fill input field
agent-browser select @ref "option"    # Select dropdown option
agent-browser hover @ref              # Hover over element
agent-browser press Enter             # Press keyboard key

Semantic Locators

agent-browser find role button "Submit"    # Find by ARIA role
agent-browser find text "Welcome"          # Find by visible text
agent-browser find label "Email"           # Find by label

Waiting

agent-browser wait visible @ref            # Wait for element visible
agent-browser wait hidden @ref             # Wait for element hidden
agent-browser wait network                 # Wait for network idle
agent-browser wait time 2000               # Wait milliseconds

Session Management

agent-browser session save mystate         # Save browser state
agent-browser session load mystate         # Load saved state
agent-browser session list                 # List saved sessions
agent-browser close                        # Close browser

Security Notes

Never commit these files:

  • *.state - Browser session state files contain cookies
  • agent-browser-profile/ - Profile directories with credentials
  • Screenshots that may contain sensitive data

Add to .gitignore:

*.state
agent-browser-profile/
.agent-browser/
screenshots/

Integration with Other Skills

With Parallel Research

# Research a topic, then verify claims on websites
parallel_research.py chat "Find pricing for Acme Corp"
# Then use agent-browser to verify on their actual pricing page
agent-browser open https://acme.com/pricing
agent-browser snapshot -i

With Screenshot Comparison

# Take baseline screenshots for visual regression
agent-browser open https://myapp.com
agent-browser screenshot baseline.png

# After changes, compare
agent-browser screenshot current.png
# Use image comparison tool

With Form Data from Sheets

# Load test data from Google Sheets, run form tests
import subprocess
test_data = get_sheet_data("Form Test Cases")
for row in test_data:
    subprocess.run(["agent-browser", "fill", "@email", row["email"]])
    subprocess.run(["agent-browser", "fill", "@password", row["password"]])
    subprocess.run(["agent-browser", "click", "@submit"])

Files in This Skill

  • references/commands.md - Full command reference
  • references/authentication.md - Login flow patterns
  • references/testing-patterns.md - E2E test workflows
  • references/snapshot-workflow.md - Ref system deep dive
  • scripts/browser_test.py - Python automation wrapper

Example: Complete Form Test

# Open the registration page
agent-browser open https://example.com/register

# Get element refs
agent-browser snapshot -i

# Fill the form (refs from snapshot output)
agent-browser fill @e1 "John Doe"
agent-browser fill @e2 "[email protected]"
agent-browser fill @e3 "SecurePass123!"
agent-browser select @e4 "United States"
agent-browser click @e5  # Terms checkbox
agent-browser click @e6  # Submit button

# Wait for navigation and verify
agent-browser wait network
agent-browser snapshot -i

# Take confirmation screenshot
agent-browser screenshot registration-success.png

Troubleshooting

Element not found:

  • Re-run snapshot -i to get fresh refs
  • Use semantic locators: agent-browser find text "Submit"
  • Check if element is in an iframe

Page not loading:

  • Increase timeout: agent-browser open <url> --timeout 30000
  • Wait for network: agent-browser wait network

Session expired:

  • Save state before tests: agent-browser session save backup
  • Load state to restore: agent-browser session load backup
how to use agent-browser

How to use agent-browser 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
2

Execute installation command

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

$npx skills add https://github.com/casper-studios/casper-marketplace --skill agent-browser

The skills CLI fetches agent-browser from GitHub repository casper-studios/casper-marketplace 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

Reload or restart Cursor to activate agent-browser. Access the skill through slash commands (e.g., /agent-browser) 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.

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

4.538 reviews
  • Kwame Abbas· Dec 24, 2024

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

  • Kwame Smith· Dec 20, 2024

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

  • Dhruvi Jain· Dec 4, 2024

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

  • Henry Perez· Dec 4, 2024

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

  • Oshnikdeep· Nov 23, 2024

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

  • Omar Martinez· Nov 23, 2024

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

  • Ama Haddad· Nov 15, 2024

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

  • Kwame Martinez· Nov 11, 2024

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

  • Ganesh Mohane· Oct 14, 2024

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

  • James Gonzalez· Oct 14, 2024

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

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