firecrawl-scraper
Overview
Deep web scraping, screenshots, PDF parsing, and website crawling using Firecrawl API
When to Use
- When you need deep content extraction from web pages
- When page interaction is required (clicking, scrolling, etc.)
- When you want screenshots or PDF parsing
- When batch scraping multiple URLs
Installation
npx skills add -g BenedictKing/firecrawl-scraper
Step-by-Step Guide
- Install the skill using the command above
- Configure Firecrawl API key
- Use naturally in Claude Code conversations
Examples
See GitHub Repository for examples.
Best Practices
- Configure API keys via environment variables
Troubleshooting
See the GitHub repository for troubleshooting guides.
Related Skills
- context7-auto-research, tavily-web, exa-search, codex-review
AGI Framework Integration
Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills
Memory-First Protocol
Cache data schemas, transformation rules, and query patterns. BM25 excels at finding specific column names, table references, and SQL patterns.
# Check for prior data engineering context before starting
python3 execution/memory_manager.py auto --query "data processing patterns and pipeline configurations for Firecrawl Scraper"
Storing Results
After completing work, store data engineering decisions for future sessions:
python3 execution/memory_manager.py store \
--content "Data pipeline: ETL from PostgreSQL to Qdrant, 50K records/batch, incremental sync via updated_at" \
--type technical --project <project> \
--tags firecrawl-scraper data
Multi-Agent Collaboration
Share data schema changes with backend and frontend agents so they update their models accordingly.
python3 execution/cross_agent_context.py store \
--agent "<your-agent>" \
--action "Data pipeline implemented — ETL processing with validation, deduplication, and error recovery" \
--project <project>