# Firecrawl Scraper

> Deep web scraping, screenshots, PDF parsing, and website crawling using Firecrawl API. Use when you need deep content extraction from web pages, page interaction is required (clicking, scrolling, etc.), or you want screenshots or PDF parsing.

- Skill: `techwavedev/firecrawl-scraper` (Agent Skill)
- Install (CLI): `npx skillmds@latest add techwavedev/firecrawl-scraper`
- Raw SKILL.md: https://api.skillmd.com/api/skills/techwavedev/firecrawl-scraper/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: techwavedev (https://skillmd.com/u/techwavedev)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/techwavedev/firecrawl-scraper

---


# 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
```bash
npx skills add -g BenedictKing/firecrawl-scraper
```

## Step-by-Step Guide
1. Install the skill using the command above
2. Configure Firecrawl API key
3. Use naturally in Claude Code conversations

## Examples
See [GitHub Repository](https://github.com/BenedictKing/firecrawl-scraper) 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-INTEGRATION-START -->

## AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/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.

```bash
# 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:

```bash
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.

```bash
python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Data pipeline implemented — ETL processing with validation, deduplication, and error recovery" \
  --project <project>
```

<!-- AGI-INTEGRATION-END -->