Intelligent web scraping with automatic strategy selection and TypeScript-first Apify Actor development.

This skill provides:

• Interactive reconnaissance - Hands-on site exploration using Playwright MCP & Chrome DevTools
• Proactive strategy discovery - Automatically checks for sitemaps and APIs
• Intelligent recommendations - Suggests optimal approach (sitemap/API/Playwright/hybrid)
• Iterative implementation - Starts simple, adds complexity only if needed
• Production-ready guidance - TypeScript-first Apify Actor development

Add this skill to Claude Code by placing this directory in the skills folder.

User: "Scrape https://example.com"

Claude will automatically:
1. Open site in browser (Playwright MCP) - observe loading behavior
2. Monitor network traffic (DevTools) - discover API endpoints
3. Test interactions - pagination, filters, dynamic content
4. Assess protections - Cloudflare, rate limits, fingerprinting
5. Check for sitemaps (/sitemap.xml, robots.txt)
6. Generate intelligence report with optimal strategy
7. Implement recommended approach iteratively
8. Test with small batch (5-10 items)
9. Scale to full dataset

User: "Make this an Apify Actor"

Claude will:
1. Recommend TypeScript (strongly)
2. Guide through `apify create` command
3. Help choose appropriate template (Cheerio vs Playwright)
4. Port scraping logic to Actor format
5. Configure input schema
6. Test and deploy

web-scraping/
├── SKILL.md                    # Main entry point (proactive workflow)
├── workflows/                  # Implementation patterns
│   ├── reconnaissance.md       # Phase 1 interactive reconnaissance (CRITICAL)
│   ├── implementation.md       # Phase 4 iterative implementation
│   └── productionization.md    # Phase 5 Actor creation
├── strategies/                 # Deep-dive guides
│   ├── sitemap-discovery.md   # 60x faster URL discovery
│   ├── api-discovery.md       # 10-100x faster than scraping
│   ├── playwright-scraping.md # Browser-based scraping
│   ├── cheerio-scraping.md    # HTTP-only (5x faster)
│   └── hybrid-approaches.md   # Combining strategies
├── examples/                   # Runnable code
│   ├── sitemap-basic.js
│   ├── api-scraper.js
│   ├── hybrid-sitemap-api.js
│   ├── playwright-basic.js
│   └── iterative-fallback.js
├── reference/                  # Quick lookup
│   ├── regex-patterns.md
│   ├── selector-guide.md
│   └── anti-patterns.md
├── apify/                      # Production deployment
│   ├── typescript-first.md    # Why TypeScript
│   ├── cli-workflow.md        # apify create (CRITICAL)
│   ├── templates/             # TypeScript boilerplate
│   └── examples/              # Working actors
└── README.md                   # This file

This skill follows Anthropic's official best practices for skill development:

Pattern: Three-level loading system to manage context efficiently

• Level 1: YAML frontmatter (~85 tokens) - Always loaded
• Level 2: Main SKILL.md (~356 lines) - Loaded when skill invoked
• Level 3: Subdirectories - Loaded on-demand as needed

Result: 70-80% token reduction vs monolithic documentation

Source: skill-creator/SKILL.md

Pattern: Write instructions using verb-first commands, not second-person language

Examples:

• ✅ "Load this workflow when user requests"
• ✅ "Check for sitemaps automatically"
• ❌ "You should load this workflow"
• ❌ "You need to check for sitemaps"

Exception: Second-person is acceptable in user-facing prompts, code comments, and tutorial examples

Source: skill-creator/SKILL.md

Pattern: Concise, specific name and description that determine when Claude invokes the skill

Applied:

• name: web-scraping - Clear, hyphen-case identifier
• description: - Specific about activation triggers and capabilities (189 chars, optimized from 244)

Source: agent_skills_spec.md

Pattern: Keep only essential procedural instructions in SKILL.md; move detailed information to subdirectories

Applied:

• SKILL.md: Core 4-phase workflow (~356 lines)
• workflows/: Detailed implementation patterns
• strategies/: Deep-dive guides
• examples/: Runnable code
• reference/: Quick lookup patterns
• apify/: Production deployment guides

Source: skill-creator/SKILL.md

Pattern: Separate executable code, documentation, and output resources

Applied:

• examples/ - Executable JavaScript learning examples (like scripts/)
• workflows/, strategies/, reference/, apify/ - Documentation loaded as needed (like references/)
• apify/templates/, apify/examples/ - Boilerplate code and templates (like assets/)

Source: skill-creator/SKILL.md

Pattern: Create focused skills for specific purposes rather than one skill that does everything

Applied: This skill focuses specifically on web scraping and Apify Actor development, not general web development

Source: Anthropic Skills Best Practices

Pattern: Use clear, technical language focused on "what" and "how" rather than persuasive or promotional tone

Applied: Direct technical guidance throughout ("Check for sitemaps", "Implement iteratively") vs. marketing language

Source: skill-creator/SKILL.md

Before any implementation:

• Playwright MCP: Open site in real browser, observe loading behavior, test interactions
• Chrome DevTools MCP: Monitor network traffic, discover hidden APIs, analyze request patterns
• Protection Analysis: Detect Cloudflare, CAPTCHA, rate limiting, fingerprinting
• Intelligence Report: Generate structured findings with optimal strategy recommendation

Why this matters: Discovers hidden APIs (10-100x faster than HTML scraping), identifies blockers before coding, provides intelligence for informed strategy selection.

Automatically validates reconnaissance findings:

• Sitemaps (/sitemap.xml, robots.txt)
• API endpoints (confirmed from DevTools analysis)
• Site structure (JavaScript-heavy? Authentication?)

Presents 2-3 options with:

• Time estimates
• Complexity rating
• Pros/cons
• Clear reasoning

• Start with simplest approach
• Test small batch (5-10 items)
• Scale or fallback based on results
• Add robustness last

For production actors:

• Strongly recommend TypeScript
• Always use apify create command
• Choose template based on site type (Cheerio for static, Playwright for JS-heavy)
• Type-safe input/output

1. User: "Scrape example.com"
2. Claude opens site with Playwright MCP (Phase 1 reconnaissance)
3. Claude monitors DevTools, finds API endpoint GET /api/products
4. Claude tests pagination, detects Cloudflare protection
5. Claude checks sitemap (validates Phase 1 findings - 1,234 URLs)
6. Claude generates intelligence report
7. Claude recommends: Hybrid (Sitemap + API + Proxies)
8. Implements with discovered API endpoints
9. Tests with 10 items
10. Scales to full dataset
11. Result: 1000 products in 5 minutes, no blocks

1. User: "Make this an Apify Actor"
2. Claude loads apify/ module
3. Recommends TypeScript? (Yes)
4. Guides through: apify create
5. Analyzes site: Static HTML → Selects Cheerio template
6. Ports scraping logic to TypeScript
7. Adds input schema
8. Tests: apify run
9. Deploys: apify push
10. Result: Production-ready actor

✅ Always start with Playwright MCP + DevTools exploration ✅ Discover APIs before attempting HTML scraping ✅ Test site interactions to understand behavior ✅ Assess protections early (Cloudflare, CAPTCHA, rate limits) ✅ Generate intelligence report with findings

✅ Validate reconnaissance with automated sitemap checks ✅ Confirm API endpoints discovered in Phase 1 ✅ Analyze site structure based on observations

✅ Start simple (sitemap → API → Playwright) ✅ Test small batch first ✅ Handle errors gracefully ✅ Respect rate limits

✅ Use TypeScript for Apify Actors ✅ Always use apify create command ✅ Choose template based on Phase 1 findings (Cheerio vs Playwright) ✅ Test locally with apify run ✅ Deploy with apify push

→ See strategies/sitemap-discovery.md troubleshooting section

→ See strategies/api-discovery.md authentication section

→ See strategies/playwright-scraping.md performance optimization

→ See apify/cli-workflow.md common issues section

• Main skill: Read SKILL.md for complete workflow
• Workflows: Implementation patterns in workflows/
• Strategies: Browse strategies/ for detailed guides
• Examples: Run code in examples/ directory
• Reference: Quick lookups in reference/
• Apify: Production deployment in apify/

Intelligence first, implementation second!

This skill prioritizes:

1. Reconnaissance - Understand before coding (APIs > Sitemaps > Scraping)
2. Speed - Fastest approach that works (API 10-100x faster than HTML)
3. Reliability - Structured data > HTML parsing
4. Maintainability - TypeScript, proper tooling
5. Best practices - Industry standards

4.0.0 - Intelligence-driven scraping:

• NEW: Interactive reconnaissance phase (Playwright MCP + Chrome DevTools)
• NEW: API discovery before HTML scraping
• NEW: Protection analysis and countermeasures
• Progressive disclosure architecture
• Proactive strategy discovery
• TypeScript-first Apify guidance
• Comprehensive examples
• Modular organization

All best practices sourced from official Anthropic documentation:

• Anthropic Skills Repository
• Agent Skills Specification
• skill-creator/SKILL.md
• Anthropic Skills Announcement

Start here: Read SKILL.md for the complete proactive workflow.