Agent skill

Browser Debugging

by MadAppGang in MadAppGang/claude-code

Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP…

MITAuto-check passedDevelopment

Install Browser Debugging

skills CLI
$ npx skills add MadAppGang/claude-code --skill browser-debugging -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install MadAppGang/claude-code browser-debugging --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/MadAppGang/claude-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/dev/skills/frontend/browser-debugging .claude/skills/browser-debugging && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
browser-debugging
GitHub stars
283
Token cost
~4.3k tokens
SKILL.md length
586 words
Files
1
Skills in repo
69
Repo updated
First seen
Licence
MIT

At a glance

Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP…

  • Mentions testing
  • SKILL.md covers When to Use This Skill, Prerequisites, Visual Analysis Models… and Recipe 1: Agent…, plus 7 more sections
  • Calls npm; needs OPENROUTER_API_KEY
  • UI verification

What it does

Browser Debugging is an agent skill from MadAppGang/claude-code. Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP tools. Use after implementing UI features, for design validation, when investigating console errors, for regression testing, or when user mentions testing, browser bugs, console errors, or UI verification.

Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Debugging, Browser extensions and QA and bug reports. It works with Chrome Extensions and Qwen. The repository describes itself as: claude code plugins marketplace. The licence is MIT.

When your agent uses it

  • Mentions testing
  • UI verification

Example prompts

  • “/browser-debugging”

Requirements

  • Node.js
  • A credential in OPENROUTER_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 6097ad4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENROUTER_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Browser Debugging loads about 4.3k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 586 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~105
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from MadAppGang/claude-code at commit 6097ad4, republished under its MIT licence (© MadAppGang). 586 words, ~4,289 tokens.

Download SKILL.mdSave it as .claude/skills/browser-debugging/SKILL.md (or your agent's skills folder).
name
browser-debugging
description
Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP tools. Use after implementing UI features, for design validation, when investigating console errors, for regression testing, or when user mentions testing, browser bugs, console errors, or UI verification.

Browser Debugging

This Skill provides comprehensive browser-based UI testing, visual analysis, and debugging capabilities using Claude-in-Chrome Extension MCP tools and optional external vision models via Claudish.

When to Use This Skill

Claude and agents (developer, reviewer, tester, ui-developer) should invoke this Skill when:

  • Validating Own Work: After implementing UI features, agents should verify their work in a real browser
  • Design Fidelity Checks: Comparing implementation screenshots against design references
  • Visual Regression Testing: Detecting layout shifts, styling issues, or visual bugs
  • Console Error Investigation: User reports console errors or warnings
  • Form/Interaction Testing: Verifying user interactions work correctly
  • Pre-Commit Verification: Before committing or deploying code
  • Bug Reproduction: User describes UI bugs that need investigation

Prerequisites

Required: Claude-in-Chrome Extension

This skill requires Claude-in-Chrome Extension MCP. The extension provides browser automation tools directly through Claude.

Check if available: The tools are available when the extension is installed and active. Look for mcp__claude-in-chrome__* tools in your available MCP tools.

Optional: External Vision Models (via OpenRouter)

For advanced visual analysis, use external vision-language models via Claudish:

bash
# Check OpenRouter API key
[[ -n "${OPENROUTER_API_KEY}" ]] && echo "OpenRouter configured" || echo "Not configured"

# Install claudish
npm install -g claudish

For best visual analysis of UI screenshots, use these models via Claudish:

ModelStrengthsCostBest For
qwen/qwen3-vl-32b-instructBest OCR, spatial reasoning, GUI automation, 32+ languages~$0.06/1M inputDesign fidelity, OCR, element detection
google/gemini-2.5-flashFast, excellent price/performance, 1M context~$0.05/1M inputReal-time validation, large pages
openai/gpt-4oMost fluid multimodal, strong all-around~$0.15/1M inputComplex visual reasoning
Tier 2: Fast & Affordable
ModelStrengthsCostBest For
qwen/qwen3-vl-30b-a3b-instructGood balance, MoE architecture~$0.04/1M inputQuick checks, multiple iterations
google/gemini-2.5-flash-liteUltrafast, very cheap~$0.01/1M inputHigh-volume testing
Tier 3: Free Options
ModelNotes
openrouter/polaris-alphaFREE, good for testing workflows
Model Selection Guide
Design Fidelity Validation → qwen/qwen3-vl-32b-instruct (best OCR & spatial)
Quick Smoke Tests → google/gemini-2.5-flash (fast & cheap)
Complex Layout Analysis → openai/gpt-4o (best reasoning)
High Volume Testing → google/gemini-2.5-flash-lite (ultrafast)
Budget Conscious → openrouter/polaris-alpha (free)

Recipe 1: Agent Self-Validation (After Implementation)

Use Case: Developer/UI-Developer agent validates their own work after implementing a feature.

Pattern: Implement → Screenshot → Analyze → Report
markdown
## After Implementing UI Feature

1. **Save file changes** (Edit tool)

2. **Capture implementation screenshot**:
   \`\`\`
   mcp__claude-in-chrome__navigate(url: "http://localhost:5173/your-route")
   # Wait for page load
   mcp__claude-in-chrome__computer(action: "screenshot")
   \`\`\`

3. **Analyze with embedded Claude** (always available):
   - Describe what you see in the screenshot
   - Check for obvious layout issues
   - Verify expected elements are present

4. **Optional: Enhanced analysis with vision model**:
   \`\`\`bash
   # Use Qwen VL for detailed visual analysis
   npx claudish --model qwen/qwen3-vl-32b-instruct --stdin --quiet <<EOF
   Analyze this UI screenshot and identify any visual issues:

   IMAGE: [screenshot from previous step]

   Check for:
   - Layout alignment issues
   - Spacing inconsistencies
   - Typography problems (font sizes, weights)
   - Color contrast issues
   - Missing or broken elements
   - Responsive design problems

   Provide specific, actionable feedback.
   EOF
   \`\`\`

5. **Check console for errors**:
   \`\`\`
   mcp__claude-in-chrome__read_console_messages()
   # Filter for errors in response
   \`\`\`

6. **Check network for failures**:
   \`\`\`
   mcp__claude-in-chrome__read_network_requests()
   # Look for failed requests (status >= 400)
   \`\`\`

7. **Report results to orchestrator**
Quick Self-Check (5-Point Validation)

Agents should perform this quick check after any UI implementation:

markdown
## Quick Self-Validation Checklist

□ 1. Screenshot shows expected UI elements
□ 2. No console errors (check: mcp__claude-in-chrome__read_console_messages)
□ 3. No network failures (check: mcp__claude-in-chrome__read_network_requests)
□ 4. Interactive elements respond correctly
□ 5. Visual styling matches expectations

Recipe 2: Design Fidelity Validation

Use Case: Compare implementation against Figma design or design reference.

Pattern: Design Reference → Implementation → Visual Diff
markdown
## Design Fidelity Check

### Step 1: Capture Implementation
\`\`\`
mcp__claude-in-chrome__navigate(url: "http://localhost:5173/component")
mcp__claude-in-chrome__resize_window(width: 1440, height: 900)
mcp__claude-in-chrome__computer(action: "screenshot")
\`\`\`

### Step 2: Visual Analysis with Vision Model

\`\`\`bash
npx claudish --model qwen/qwen3-vl-32b-instruct --stdin --quiet <<EOF
Compare these two UI screenshots and identify design fidelity issues:

DESIGN REFERENCE: /tmp/design-reference.png
IMPLEMENTATION: [screenshot from step 1]

Analyze and report differences in:

## Colors & Theming
- Background colors (exact hex values)
- Text colors (headings, body, muted)
- Border and divider colors
- Button/interactive element colors

## Typography
- Font families
- Font sizes (px values)
- Font weights (regular, medium, bold)
- Line heights
- Letter spacing

## Spacing & Layout
- Padding (top, right, bottom, left)
- Margins between elements
- Gap spacing in flex/grid
- Container max-widths
- Alignment (center, left, right)

## Visual Elements
- Border radius values
- Box shadows (blur, spread, color)
- Icon sizes and colors
- Image aspect ratios

## Component Structure
- Missing elements
- Extra elements
- Wrong element order

For EACH difference found, provide:
1. Category (colors/typography/spacing/visual/structure)
2. Severity (CRITICAL/MEDIUM/LOW)
3. Expected value (from design)
4. Actual value (from implementation)
5. Specific Tailwind CSS fix

Output as structured markdown.
EOF
\`\`\`

### Step 3: Generate Fix Recommendations

Parse vision model output and create actionable fixes for ui-developer agent.

Recipe 3: Interactive Element Testing

Use Case: Verify buttons, forms, and interactive components work correctly.

Show full SKILL.md (233 more words)Show less
Pattern: Snapshot → Interact → Verify → Report
markdown
## Interactive Testing Flow

### Step 1: Get Page Structure
\`\`\`
mcp__claude-in-chrome__read_page()
# Returns DOM structure with element references
\`\`\`

### Step 2: Test Each Interactive Element

**Button Test**:
\`\`\`
# Before
mcp__claude-in-chrome__computer(action: "screenshot")

# Find and click button (natural language)
mcp__claude-in-chrome__find(description: "submit button")
mcp__claude-in-chrome__computer(action: "left_click", coordinate: [x, y])

# OR click by reference
mcp__claude-in-chrome__computer(action: "click", ref: "button[type=submit]")

# After (wait for response)
# Wait a moment for response
mcp__claude-in-chrome__computer(action: "screenshot")

# Check results
mcp__claude-in-chrome__read_console_messages()
mcp__claude-in-chrome__read_network_requests()
\`\`\`

**Form Test**:
\`\`\`
# Fill form fields
mcp__claude-in-chrome__form_input(
  selector: "#email",
  value: "test@example.com"
)
mcp__claude-in-chrome__form_input(
  selector: "#password",
  value: "SecurePass123!"
)

# Submit (click button)
mcp__claude-in-chrome__find(description: "submit button")
mcp__claude-in-chrome__computer(action: "left_click", coordinate: [x, y])

# Verify success
mcp__claude-in-chrome__read_page()
# Check for success indicators
\`\`\`

**Hover State Test**:
\`\`\`
mcp__claude-in-chrome__computer(action: "screenshot")
mcp__claude-in-chrome__find(description: "primary button")
mcp__claude-in-chrome__computer(action: "hover", coordinate: [x, y])
mcp__claude-in-chrome__computer(action: "screenshot")
# Compare screenshots for hover state changes
\`\`\`

### Step 3: Analyze Interaction Results

Use vision model to compare before/after screenshots:
\`\`\`bash
npx claudish --model google/gemini-2.5-flash --stdin --quiet <<EOF
Compare these before/after screenshots and verify the interaction worked:

BEFORE: [screenshot before interaction]
AFTER: [screenshot after interaction]

Expected behavior: [describe what should happen]

Verify:
1. Did the expected UI change occur?
2. Are there any error states visible?
3. Did loading states appear/disappear correctly?
4. Is the final state correct?

Report: PASS/FAIL with specific observations.
EOF
\`\`\`

Recipe 4: Responsive Design Validation

Use Case: Verify UI works across different screen sizes.

Pattern: Resize → Screenshot → Analyze
markdown
## Responsive Testing

### Breakpoints to Test

| Breakpoint | Width | Description |
|------------|-------|-------------|
| Mobile | 375px | iPhone SE |
| Mobile L | 428px | iPhone 14 Pro Max |
| Tablet | 768px | iPad |
| Desktop | 1280px | Laptop |
| Desktop L | 1920px | Full HD |

### Automated Responsive Check

\`\`\`bash
#!/bin/bash
# Test all breakpoints

BREAKPOINTS=(375 428 768 1280 1920)
URL="http://localhost:5173/your-route"

for width in "\${BREAKPOINTS[@]}"; do
  echo "Testing \${width}px..."

  # Navigate (once)
  mcp__claude-in-chrome__navigate(url: "$URL")

  # Resize and screenshot
  mcp__claude-in-chrome__resize_window(width: $width, height: 900)
  mcp__claude-in-chrome__computer(action: "screenshot")
  # Save/analyze screenshot
done
\`\`\`

### Visual Analysis for Responsive Issues

\`\`\`bash
npx claudish --model qwen/qwen3-vl-32b-instruct --stdin --quiet <<EOF
Analyze these responsive screenshots for layout issues:

MOBILE (375px): [screenshot 1]
TABLET (768px): [screenshot 2]
DESKTOP (1280px): [screenshot 3]

Check for:
1. Text overflow or truncation
2. Elements overlapping
3. Improper stacking on mobile
4. Touch targets too small (<44px)
5. Hidden content that shouldn't be hidden
6. Horizontal scroll issues
7. Image scaling problems

Report issues by breakpoint with specific CSS fixes.
EOF
\`\`\`

Recipe 5: Accessibility Validation

Use Case: Verify accessibility standards (WCAG 2.1 AA).

Pattern: Snapshot → Analyze → Check Contrast
markdown
## Accessibility Check

### Automated A11y Testing

\`\`\`
# Get full page content for accessibility tree analysis
mcp__claude-in-chrome__read_page()

# Get all text content
mcp__claude-in-chrome__get_page_text()

# Check for common issues:
# - Missing alt text (look for img without alt in read_page)
# - Missing ARIA labels
# - Incorrect heading hierarchy
# - Missing form labels
\`\`\`

### Visual Contrast Analysis

\`\`\`bash
npx claudish --model qwen/qwen3-vl-32b-instruct --stdin --quiet <<EOF
Analyze this screenshot for accessibility issues:

IMAGE: [screenshot]

Check WCAG 2.1 AA compliance:

1. **Color Contrast**
   - Text contrast ratio (need 4.5:1 for normal, 3:1 for large)
   - Interactive element contrast
   - Focus indicator visibility

2. **Visual Cues**
   - Do links have underlines or other visual differentiation?
   - Are error states clearly visible?
   - Are required fields indicated?

3. **Text Readability**
   - Font size (minimum 16px for body)
   - Line height (minimum 1.5)
   - Line length (max 80 characters)

4. **Touch Targets**
   - Minimum 44x44px for interactive elements
   - Adequate spacing between targets

Report violations with severity and specific fixes.
EOF
\`\`\`

Recipe 6: Console & Network Debugging

Use Case: Investigate runtime errors and API issues.

Pattern: Monitor → Capture → Analyze
markdown
## Debug Session

### Real-Time Console Monitoring

\`\`\`
# Get all console messages
mcp__claude-in-chrome__read_console_messages()

# Response includes:
# - Type (log, warn, error, info)
# - Message content
# - Timestamp
# - Stack trace (for errors)
\`\`\`

### Network Request Analysis

\`\`\`
# Get all network requests
mcp__claude-in-chrome__read_network_requests()

# Response includes:
# - URL
# - Method (GET, POST, etc.)
# - Status code
# - Response time
# - Request/response headers
# - Request/response body (if available)
\`\`\`

### Error Pattern Analysis

Common error patterns to look for:

| Error Type | Pattern | Common Cause |
|------------|---------|--------------|
| React Error | "Cannot read property" | Missing null check |
| React Error | "Invalid hook call" | Hook rules violation |
| Network Error | "CORS" | Missing CORS headers |
| Network Error | "401" | Auth token expired |
| Network Error | "404" | Wrong API endpoint |
| Network Error | "500" | Server error |

Quick Reference: Claude-in-Chrome MCP Tools

Navigation
  • navigate(url) - Load URL in current tab
  • tabs_create_mcp(url) - Open new tab
  • tabs_context_mcp() - List all tabs
Inspection
  • read_page() - Get DOM structure with element references
  • get_page_text() - Extract all visible text
  • computer(action: "screenshot") - Capture visual state
Interaction
  • computer(action: "left_click", coordinate: [x, y]) - Click at coordinates
  • computer(action: "click", ref: "selector") - Click by CSS selector
  • computer(action: "hover", coordinate: [x, y]) - Hover at coordinates
  • form_input(selector, value) - Fill input field
  • computer(action: "type", text: "...") - Type text
  • computer(action: "key", key: "Enter") - Press key
Console & Network
  • read_console_messages() - Get console output
  • read_network_requests() - Get network activity
Advanced
  • javascript_tool(script) - Execute JavaScript in page
  • resize_window(width, height) - Change viewport size
  • find(description) - Find element by natural language
  • gif_creator(start/stop) - Record interactions as GIF
  • upload_image(selector, imagePath) - Upload image file
  • shortcuts_list() - List keyboard shortcuts
  • shortcuts_execute(shortcut) - Execute keyboard shortcut

Integration with Agents

For Developer Agent

After implementing any UI feature, the developer agent should:

markdown
## Developer Self-Validation Protocol

1. Save code changes
2. Navigate to the page: \`mcp__claude-in-chrome__navigate\`
3. Take screenshot: \`mcp__claude-in-chrome__computer(action: "screenshot")\`
4. Check console: \`mcp__claude-in-chrome__read_console_messages()\`
5. Check network: \`mcp__claude-in-chrome__read_network_requests()\`
6. Report: "Implementation verified - [X] console errors, [Y] network failures"
For Reviewer Agent

When reviewing UI changes:

markdown
## Reviewer Validation Protocol

1. Read the code changes
2. Navigate to affected pages
3. Take screenshots of all changed components
4. Use vision model for visual analysis (if design reference available)
5. Check console for new errors introduced
6. Verify no regression in existing functionality
7. Report: "Visual review complete - [findings]"
For Tester Agent

Comprehensive testing:

markdown
## Tester Validation Protocol

1. Navigate to test target
2. Get page structure for element references
3. Execute test scenarios (interactions, forms, navigation)
4. Capture before/after screenshots for each action
5. Monitor console throughout
6. Monitor network throughout
7. Use vision model for visual regression detection
8. Generate detailed test report
For UI-Developer Agent

After fixing UI issues:

markdown
## UI-Developer Validation Protocol

1. Apply CSS/styling fixes
2. Take screenshot of fixed component
3. Compare with design reference using vision model
4. Verify fix doesn't break other viewports (responsive check)
5. Check console for any styling-related errors
6. Report: "Fix applied and verified - [before/after comparison]"

  • react-typescript - React component patterns
  • tanstack-router - Navigation and routing
  • shadcn-ui - Component library usage
  • testing-frontend - Automated testing strategies

© MadAppGang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/dev/skills/frontend/browser-debugging of MadAppGang/claude-code.

Open the folder on GitHubat commit 6097ad4

Compare with similar skills

Browser Debugging next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Browser Debugging compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Browser Debugging this skillMadAppGang/claude-code283—~4.3kAutomated safety check: PassMIT
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Windows QA EngineerCodeAlive-AI/ai-driven-development155—~1.4kAutomated safety check: PassMIT
Competitor Monitorhanzili/hanzi-browse177—~2.8kAutomated safety check: PassCustom licence
Claude in Chrome MCP Troubleshootingtrailofbits/skills7.4k3 repos~2.6kAutomated safety check: PassCC-BY-SA-4.0
Sentry Crash Analysishyvanmielenpelit/GnollHack161—~222Automated safety check: PassCustom licence

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Categories

Questions about Browser Debugging

What does Browser Debugging do?

Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP…. Browser Debugging is an agent skill from MadAppGang/claude-code. Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP tools.

When should I use Browser Debugging?

Browser Debugging fits situations like: mentions testing; UI verification.

How do I install Browser Debugging in Claude Code?

Run `npx skills add MadAppGang/claude-code --skill browser-debugging -a claude-code`. Or copy the skill folder (plugins/dev/skills/frontend/browser-debugging in MadAppGang/claude-code) into .claude/skills/browser-debugging in your project. Claude Code loads it when a task matches its description.

How do I install Browser Debugging in Codex?

Run `npx skills add MadAppGang/claude-code --skill browser-debugging -a codex`. Or copy the skill folder (plugins/dev/skills/frontend/browser-debugging in MadAppGang/claude-code) into .agents/skills/browser-debugging in your project. Codex loads it when a task matches its description.

Can I use Browser Debugging in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MadAppGang/claude-code --skill browser-debugging -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/browser-debugging, .gemini/skills/browser-debugging, .github/skills/browser-debugging and .opencode/skills/browser-debugging in your project.

What does Browser Debugging need to run?

Going by SKILL.md and its folder, Browser Debugging needs the command-line tools its instructions call (npm) and credentials named OPENROUTER_API_KEY. Our summary lists: Node.js; A credential in OPENROUTER_API_KEY.

Does Browser Debugging access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Browser Debugging safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Browser Debugging use?

Browser Debugging is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Browser Debugging use?

About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Browser Debugging?

Skills that share tags, products or a category with Browser Debugging: Extension Puppeteer Debugging (mengxi-ream/read-frog, 10k stars), Windows QA Engineer (CodeAlive-AI/ai-driven-development, 155 stars), Competitor Monitor (hanzili/hanzi-browse, 177 stars) and Claude in Chrome MCP Troubleshooting (trailofbits/skills, 7.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Browser Debugging?

MadAppGang (a GitHub organization) maintains it in MadAppGang/claude-code, which has 283 GitHub stars. The repository holds 69 skills in this directory. The repository was last updated on March 15, 2026.

Source: MadAppGang/claude-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.