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name: firecrawl-agent description: Perform autonomous deep web research using Firecrawl's agent. Searches, navigates, and extracts data from websites without needing URLs. Use when users need web research, company information, competitive analysis, or structured data extraction from the web. license: MIT compatibility: Requires Python 3.9+, firecrawl-py package, and FIRECRAWL_API_KEY environment variable metadata: author: ethanolivertroy version: "1.0.0" allowed-tools: Bash(python:*) Read

Firecrawl Agent Skill

This skill enables autonomous deep web research using Firecrawl's /agent endpoint. The agent can search, navigate, and extract structured data from websites without requiring URLs upfront.

When to Use This Skill

Use this skill when you need to:

• Research companies - Find founders, funding, employee counts, tech stacks
• Gather competitive intelligence - Compare products, pricing, features
• Extract structured data - Get specific information in a defined schema
• Answer questions requiring web research - When information isn't in your knowledge base

Quick Start

Run a simple research query:

Copycd firecrawl-agent/scripts
python firecrawl_agent.py "Find the founders and founding year of Anthropic"

Prerequisites

1. Install dependencies:

   Copypip install -r scripts/requirements.txt
   

2. Set API key:

   Copyexport FIRECRAWL_API_KEY=your_api_key_here
   

   Get your API key at: https://www.firecrawl.dev/

Usage

Basic Research (No Schema)

Copypython scripts/firecrawl_agent.py "What are the main features of Notion?"

Research with Structured Output

For predictable, structured responses, provide a JSON schema:

Copypython scripts/firecrawl_agent.py \
  "Find information about Stripe" \
  --schema '{"company_name": "string", "founded_year": "number", "founders": ["string"], "headquarters": "string"}'

Command Line Options

Model Selection

• spark-1-mini (default): Faster, cheaper, good for straightforward queries
• spark-1-pro: More capable, better for complex research requiring deeper navigation

Copy# Use pro model for complex research
python scripts/firecrawl_agent.py \
  "Compare the pricing tiers of Notion, Coda, and Obsidian" \
  --model spark-1-pro

Providing Starting URLs

If you know relevant URLs, provide them to focus the search:

Copypython scripts/firecrawl_agent.py \
  "Extract the pricing information" \
  --urls "https://stripe.com/pricing,https://stripe.com/enterprise"

Common Use Cases

Company Research

Copypython scripts/firecrawl_agent.py \
  "Research Anthropic: founders, funding rounds, key products, and employee count" \
  --schema '{"name": "string", "founders": ["string"], "funding_total": "string", "products": ["string"], "employee_count": "string"}'

Product Comparison

Copypython scripts/firecrawl_agent.py \
  "Compare Vercel and Netlify deployment platforms" \
  --model spark-1-pro

Contact Information

Copypython scripts/firecrawl_agent.py \
  "Find contact information for Acme Corp" \
  --schema '{"email": "string", "phone": "string", "address": "string", "social_links": ["string"]}'

Output Format

The script outputs JSON with the following structure:

Copy{
  "success": true,
  "status": "completed",
  "data": {
    // Your extracted data here
  },
  "sources": [
    "https://example.com/page1",
    "https://example.com/page2"
  ],
  "credits_used": 12
}

Error Handling

Common errors and solutions:

Cost Management

• The agent uses credits based on complexity and pages visited
• Free tier: 5 runs per day
• Set --max-credits to cap spending:

  Copypython scripts/firecrawl_agent.py "Research topic" --max-credits 25
  

Reference Documentation

• See references/REFERENCE.md for complete API parameter documentation
• See references/SCHEMAS.md for common schema patterns
• See assets/example_schemas/ for ready-to-use Pydantic models

Notes

• Firecrawl agent is in "research preview" - pricing is dynamic
• Results are available for 24 hours after completion
• Complex queries may take 30-60 seconds to complete