web-scraper

agentbay-ai/agentbay-skills · updated Apr 8, 2026

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$npx skills add https://github.com/agentbay-ai/agentbay-skills --skill web-scraper
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summary

Fetch web page content (text + images) and save as HTML or Markdown locally.

skill.md

Web Scraper

Fetch web page content (text + images) and save as HTML or Markdown locally.

Minimal dependencies: Only requires requests and beautifulsoup4 - no browser automation.

Default behavior: Downloads images to local images/ directory automatically.

Quick start

Single page

{baseDir}/scripts/scrape.py --url "https://example.com" --format html --output /tmp/page.html
{baseDir}/scripts/scrape.py --url "https://example.com" --format md --output /tmp/page.md

Recursive (follow links)

{baseDir}/scripts/scrape.py --url "https://docs.example.com" --format md --recursive --max-depth 2 --output ~/Downloads/docs-archive

Setup

Requires Python 3.8+ and minimal dependencies:

cd {baseDir}
pip install -r requirements.txt

Or install manually:

pip install requests beautifulsoup4

Note: No browser or driver needed - uses pure HTTP requests.

Inputs to collect

Single page mode

  • URL: The web page to scrape (required)
  • Format: html or md (default: html)
  • Output path: Where to save the file (default: current directory with auto-generated name)
  • Images: Downloads images by default (use --no-download-images to disable)

Recursive mode (--recursive)

  • URL: Starting point for recursive scraping
  • Format: html or md
  • Output directory: Where to save all scraped pages
  • Max depth: How many levels deep to follow links (default: 2)
  • Max pages: Maximum total pages to scrape (default: 50)
  • Domain filter: Whether to stay within same domain (default: yes)
  • Images: Downloads images by default

Conversation Flow

  1. Ask user for the URL to scrape
  2. Ask preferred output format (HTML or Markdown)
    • Note: Both formats include text and images by default
    • HTML: Preserves original structure with downloaded images
    • Markdown: Clean text format with downloaded images in images/ folder
  3. For recursive mode: Ask max depth and max pages (optional, has sensible defaults)
  4. Ask where to save (or suggest a default path like /tmp/ or ~/Downloads/)
  5. Run the script and confirm success
  6. Show the saved file/directory path

Examples

Single Page Scraping

Save as HTML

{baseDir}/scripts/scrape.py --url "https://docs.openclaw.ai/start/quickstart" --format html --output ~/Downloads/openclaw-quickstart.html

Save as Markdown (with images, default)

{baseDir}/scripts/scrape.py --url "https://en.wikipedia.org/wiki/Web_scraping" --format md --output ~/Documents/web-scraping.md

Result: Creates web-scraping.md + images/ folder with all downloaded images (text + images).

Without downloading images (optional)

{baseDir}/scripts/scrape.py --url "https://example.com" --format md --no-download-images

Result: Only text + image URLs (not downloaded locally).

Auto-generate filename

{baseDir}/scripts/scrape.py --url "https://example.com" --format html
# Saves to: example-com-{timestamp}.html

Recursive Scraping

Basic recursive crawl (depth 2, same domain, with images)

{baseDir}/scripts/scrape.py --url "https://docs.example.com" --format md --recursive --output ~/Downloads/docs-archive

Output structure (text + images for all pages):

docs-archive/
├── index.md
├── getting-started.md
├── api/
│   ├── authentication.md
│   └── endpoints.md
└── images/              # Shared images from all pages
    ├── logo.png
    └── diagram.svg

Deep crawl with custom limits

{baseDir}/scripts/scrape.py \
  --url "https://blog.example.com" \
  --format html \
  --recursive \
  --max-depth 3 \
  --max-pages 100 \
  --output ~/Archives/blog-backup

Ignore robots.txt (use with caution)

{baseDir}/scripts/scrape.py \
  --url "https://example.com" \
  --format md \
  --recursive \
  --no-respect-robots \
  --rate-limit 1.0

Faster scraping (reduced rate limit)

{baseDir}/scripts/scrape.py \
  --url "https://yoursite.com" \
  --format md \
  --recursive \
  --rate-limit 0.2

Features

Single Page Mode

  • HTML output: Preserves original page structure
    • ✅ Clean, readable HTML document
    • ✅ All images downloaded to images/ folder
    • ✅ Suitable for offline viewing
  • Markdown output: Extracts clean text content
    • Auto-downloads images to local images/ directory (default)
    • ✅ Converts image URLs to relative paths
    • ✅ Clean, readable format for archiving
    • ✅ Fallback to original URLs if download fails
    • Use --no-download-images flag to keep original URLs only
  • Simple and fast: Pure HTTP requests, no browser needed
  • Auto filename: Generates safe filename from URL if not specified

Recursive Mode (--recursive)

  • ✅ Intelligent link discovery: Automatically follows all links on crawled pages
  • ✅ Depth control: --max-depth limits how many levels deep to crawl (default: 2)
  • ✅ Page limit: --max-pages caps total pages to prevent runaway crawls (default: 50)
  • ✅ Domain filtering: --same-domain keeps crawl within starting domain (default: on)
  • ✅ robots.txt compliance: Respects site's crawling rules by default
  • ✅ Rate limiting: --rate-limit adds delay between requests (default: 0.5s)
  • ✅ Smart URL filtering: Skips images, scripts, CSS, and duplicate URLs
  • ✅ Progress tracking: Real-time console output with success/fail/skip counts
  • ✅ Organized output: Preserves URL structure in directory hierarchy
  • ✅ Efficient crawling: Sequential with rate limiting to respect servers

Guardrails

Single Page Mode

  • Respect robots.txt and site terms of service
  • Some sites may block automated access; this tool uses standard HTTP requests
  • Large pages with many images may take time to download

Recursive Mode

  • Start small: Test with --max-depth 1 --max-pages 10 first
  • Respect robots.txt: Default is on; only use --no-respect-robots for your own sites
  • Rate limiting: Default 0.5s is polite; don't go below 0.2s for public sites
  • Same domain: Strongly recommended to keep --same-domain enabled
  • Monitor progress: Watch for high fail rates (may indicate blocking)
  • Storage: Recursive crawls can generate many files; ensure sufficient disk space
  • Legal: Ensure you have permission to crawl and archive the target site

Troubleshooting

  • Connection errors: Check your internet connection and URL validity
  • 403/blocked: Some sites block scrapers; the tool uses realistic User-Agent headers
  • Timeout: Increase --timeout flag for slow-loading pages (value in seconds)
  • Image download fails: Images will fall back to original URLs
  • Missing images: Some sites use JavaScript to load images dynamically (not supported)
how to use web-scraper

How to use web-scraper 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 web-scraper
2

Execute installation command

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

$npx skills add https://github.com/agentbay-ai/agentbay-skills --skill web-scraper

The skills CLI fetches web-scraper from GitHub repository agentbay-ai/agentbay-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/web-scraper

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

4.557 reviews
  • Ira Rao· Dec 28, 2024

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

  • Ira Patel· Dec 24, 2024

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

  • Chaitanya Patil· Dec 20, 2024

    web-scraper reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Fatima Reddy· Dec 16, 2024

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

  • Diya Yang· Nov 19, 2024

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

  • Evelyn Khanna· Nov 15, 2024

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

  • Piyush G· Nov 11, 2024

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

  • Neel Reddy· Nov 7, 2024

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

  • Aditi Diallo· Oct 26, 2024

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

  • Hassan White· Oct 10, 2024

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

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