Agent skill · Data & Analytics

firecrawl-agent

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.

majiayu000github.com/majiayu000GitHub ↗
claude-coderead-onlyMIT
Install
npx skills add majiayu000/claude-skill-registry --skill firecrawl-agent --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 5 KB
Bundled scripts: none
Version: 1.0.0
Declared author: ethanolivertroy
Allowed tools: Bash(python:*)Read
Requires: Requires Python 3.9+, firecrawl-py package, and FIRECRAWL_API_KEY environment variable
Path: skills/analysis/firecrawl-agent/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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: ```bash cd firecrawl-agent/scripts python firecrawl_agent.py "Find the founders and founding year of Anthropic" ``` ## Prerequisites 1. **Install dependencies**: ```bash pip install -r scripts/requirements.txt ``` 2. **Set API key**: ```bash export FIRECRAWL_API_KEY=your_api_key_here ``` Get your API key at: https://www.firecrawl.dev/ ## Usage ### Basic Research (No Schema) ```bash python scripts/firecrawl_agent.py "What are the main features of Notion?" ``` ### Research with Structured Output For predictable, structured responses, provide a JSON sc

What's inside
Steps it walks through
  1. When to Use This Skill
  2. Quick Start
  3. Prerequisites
  4. Usage
  5. Basic Research (No Schema)
  6. Research with Structured Output
  7. Command Line Options
  8. Model Selection
  9. Providing Starting URLs
  10. Common Use Cases
  11. Company Research
  12. Product Comparison
  13. Contact Information
  14. Output Format
Ships with 1 file
  • metadata.json
Commands it runs
cd firecrawl-agent/scripts
python firecrawl_agent.py "Find the founders and founding year of Anthropic"
pip install -r scripts/requirements.txt
export FIRECRAWL_API_KEY=your_api_key_here
python scripts/firecrawl_agent.py "What are the main features of Notion?"
python scripts/firecrawl_agent.py \
Use pro model for complex research
python scripts/firecrawl_agent.py "Research topic" --max-credits 25
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About this skill
What does the firecrawl-agent skill do?

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.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill firecrawl-agent --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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