Firecrawl agent

Skill bg-szy/TOP-SKILLS/skills/marketplace/firecrawl-agent

AI-powered autonomous data extraction that navigates complex sites and returns structured JSON. Use this skill when the user wants structured data from websites, needs to extract pricing tiers, product listings, directory entries, or any data as JSON with a schema. Triggers on "extract structured data", "get all the products", "pull pricing info", "extract as JSON", or when the user provides a JSON schema for website data. More powerful than simple scraping for multi-page structured extraction.From its SKILL.md

Install

npx -y skills add bg-szy/TOP-SKILLS --skill firecrawl-agent

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SKILL.md

2.7 KB, 490 tokens by cl100k_base, as published. Nobody here has run it

firecrawl agent

AI-powered autonomous extraction. The agent navigates sites and extracts structured data (takes 2-5 minutes).

When to use

You need structured data from complex multi-page sites
Manual scraping would require navigating many pages
You want the AI to figure out where the data lives

Quick start

# Extract structured data
firecrawl agent "extract all pricing tiers" --wait -o .firecrawl/pricing.json

# With a JSON schema for structured output
firecrawl agent "extract products" --schema '{"type":"object","properties":{"name":{"type":"string"},"price":{"type":"number"}}}' --wait -o .firecrawl/products.json

# Focus on specific pages
firecrawl agent "get feature list" --urls "<url>" --wait -o .firecrawl/features.json

Options

Option	Description
`--urls <urls>`	Starting URLs for the agent
`--model <model>`	Model to use: spark-1-mini or spark-1-pro
`--schema <json>`	JSON schema for structured output
`--schema-file <path>`	Path to JSON schema file
`--max-credits <n>`	Credit limit for this agent run
`--wait`	Wait for agent to complete
`--pretty`	Pretty print JSON output
`-o, --output <path>`	Output file path

Tips

Always use --wait to get results inline. Without it, returns a job ID.
Use --schema for predictable, structured output — otherwise the agent returns freeform data.
Agent runs consume more credits than simple scrapes. Use --max-credits to cap spending.
For simple single-page extraction, prefer scrape — it's faster and cheaper.

What ships with it: 1 file

22.6 KB alongside SKILL.md

skill-report.json22.6 KB

Gives 0 of the 12 instructions most context ai engineering skills give in 490 tokens

Counted across 1,328 of the 2,349 authors here whose files we hold, read 2026-09-06

Dispatch a fresh subagent for each taskin 76 of 1328, across 59 files
Perform spec compliance review before code quality reviewin 44 of 1328, across 34 files
Dispatch a final code reviewer after all tasksin 38 of 1328, across 26 files
Answer subagent questions before allowing implementationin 36 of 1328, across 26 files
Use the least powerful model capable of the taskin 33 of 1328, across 26 files
Create a TodoWrite list for all tasksin 32 of 1328, across 22 files
Perform a task review after each implementationin 31 of 1328, across 24 files
Extract all tasks and context from the planin 29 of 1328, across 20 files
Provide full task text to subagentsin 28 of 1328, across 20 files
Use git worktrees for isolated workspacesin 25 of 1328, across 20 files
Specify the model explicitly when dispatching a subagentin 23 of 1328, across 18 files
Execute all tasks from the plan without stoppingin 21 of 1328, across 16 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.