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Firecrawl Core Workflow B — Extract, Batch & Map

firecrawl-core-workflow-b

Execute Firecrawl secondary workflow: LLM extraction, batch scraping,

SKILL.md

Full skill instructions

Firecrawl Core Workflow B — Extract, Batch & Map

Overview

Secondary workflow complementing the scrape/​crawl workflow. Covers LLM-powered structured data extraction with JSON schemas, batch scraping multiple known URLs, and rapid site map discovery. Use this when you need typed data rather than raw markdown.

Prerequisites

  • @mendable/​firecrawl-js installed
  • FIRECRAWL_API_KEY environment variable set
  • Understanding of JSON Schema (for extract)

Instructions

Step 1: LLM Extract — Structured Data from Pages

import FirecrawlApp from "@mendable/​firecrawl-js";

const firecrawl = new FirecrawlApp({
  apiKey: process.env.FIRECRAWL_API_KEY!,
});

// Extract structured data using an LLM + JSON schema
const result = await firecrawl.scrapeUrl("https://firecrawl.dev/​pricing", {
  formats: ["extract"],
  extract: {
    schema: {
      type: "object",
      properties: {
        plans: {
          type: "array",
          items: {
            type: "object",
            properties: {
              name: { type: "string" },
              price: { type: "string" },
              credits_per_month: { type: "number" },
              features: { type: "array", items: { type: "string" } },
            },
            required: ["name", "price"],
          },
        },
      },
    },
  },
});

console.log("Extracted plans:", JSON.stringify(result.extract, null, 2));

Step 2: Extract with Prompt (No Schema)

// Use natural language prompt instead of rigid schema
const result = await firecrawl.scrapeUrl("https://news.ycombinator.com", {
  formats: ["extract"],
  extract: {
    prompt: "Extract the top 5 stories with their title, URL, points, and comment count",
  },
});

console.log(result.extract);

Step 3: Batch Scrape Known URLs

// Scrape multiple specific URLs at once — more efficient than individual calls
const batchResult = await firecrawl.batchScrapeUrls(
  [
    "https://docs.firecrawl.dev/​features/​scrape",
    "https://docs.firecrawl.dev/​features/​crawl",
    "https://docs.firecrawl.dev/​features/​extract",
    "https://docs.firecrawl.dev/​features/​map",
  ],
  {
    formats: ["markdown"],
    onlyMainContent: true,
  }
);

for (const page of batchResult.data || []) {
  console.log(`${page.metadata?.title}: ${page.markdown?.length} chars`);
}

Step 4: Async Batch Scrape (Large Sets)

// Start async batch scrape for many URLs — returns job ID
const job = await firecrawl.asyncBatchScrapeUrls(
  urls,  // array of 100+ URLs
  { formats: ["markdown"] }
);

// Poll for completion
let status = await firecrawl.checkBatchScrapeStatus(job.id);
while (status.status !== "completed") {
  await new Promise(r => setTimeout(r, 5000));
  status = await firecrawl.checkBatchScrapeStatus(job.id);
}

console.log(`Batch complete: ${status.data?.length} pages`);

Step 5: Map — Rapid URL Discovery

// Discover all URLs on a site in ~2-3 seconds
// Uses sitemap.xml + SERP + cached crawl data
const mapResult = await firecrawl.mapUrl("https://docs.firecrawl.dev");

const urls = mapResult.links || [];
console.log(`Discovered ${urls.length} URLs`);

// Categorize by section
const sections = {
  docs: urls.filter(u => u.includes("/​docs/")),
  api: urls.filter(u => u.includes("/​api-reference/")),
  features: urls.filter(u => u.includes("/​features/")),
  other: urls.filter(u => !u.includes("/​docs/") && !u.includes("/​api-reference/")),
};

Object.entries(sections).forEach(([name, list]) => {
  console.log(`  ${name}: ${list.length} URLs`);
});

Step 6: Map + Selective Scrape Pipeline

// 1. Map to discover URLs, 2. Filter, 3. Batch scrape relevant ones
async function intelligentScrape(siteUrl: string, pathFilter: string) {
  const map = await firecrawl.mapUrl(siteUrl);
  const relevant = (map.links || []).filter(url => url.includes(pathFilter));

  console.log(`Map found ${map.links?.length} URLs, ${relevant.length} match filter`);

  if (relevant.length === 0) return [];
  if (relevant.length <= 10) {
    return firecrawl.batchScrapeUrls(relevant, { formats: ["markdown"] });
  }

  // For large sets, use async batch
  const job = await firecrawl.asyncBatchScrapeUrls(relevant.slice(0, 100), {
    formats: ["markdown"],
  });
  // ...poll for completion
  return job;
}

await intelligentScrape("https://docs.firecrawl.dev", "/​features/");

Output

  • Typed JSON objects extracted from web pages
  • Batch scrape results for multiple URLs
  • Complete site URL map for discovery
  • Filtered scrape pipeline combining map + batch

Error Handling

ErrorCauseSolution
Empty extractPage content too complex for LLMSimplify schema, shorten prompt
Inconsistent extractionPrompt too longKeep prompts short and focused
Batch scrape timeoutToo many URLsUse async batch with polling
Map returns few URLsSite has no sitemap.xmlUse crawlUrl for thorough discovery
402 Payment RequiredCredits exhaustedReduce batch size, check balance

Examples

Extract Products from E-Commerce

const products = await firecrawl.scrapeUrl("https://store.example.com/​products", {
  formats: ["extract"],
  extract: {
    schema: {
      type: "object",
      properties: {
        products: {
          type: "array",
          items: {
            type: "object",
            properties: {
              name: { type: "string" },
              price: { type: "number" },
              availability: { type: "string" },
            },
            required: ["name", "price"],
          },
        },
      },
    },
  },
});

Resources

Next Steps

For common errors, see firecrawl-common-errors.

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