AGENT SKILL

firecrawl-performance-tuning

Optimize FireCrawl API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for FireCrawl integrations. Trigger with phrases like "firecrawl performance", "optimize firecrawl", "firecrawl latency", "firecrawl caching", "firecrawl slow", "firecrawl batch".

License 许可
MIT
最近更新
2026-03-20
Stars
★ 4
Forks
0

01 前言 Front Matter

name
firecrawl-performance-tuning
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
version
1.0.0
description
Optimize FireCrawl API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for FireCrawl integrations. Trigger with phrases like "firecrawl performance", "optimize firecrawl", "firecrawl latency", "firecrawl caching", "firecrawl slow", "firecrawl batch".
allowed-tools
Read, Write, Edit
compatible-with
claude-code, codex, openclaw

03 SKILL.md 正文

FireCrawl Performance Tuning

Overview

Optimize FireCrawl API performance with caching, batching, and connection pooling.

Prerequisites

  • FireCrawl SDK installed
  • Understanding of async patterns
  • Redis or in-memory cache available (optional)
  • Performance monitoring in place

Latency Benchmarks

Operation P50 P95 P99
Read 50ms 150ms 300ms
Write 100ms 250ms 500ms
List 75ms 200ms 400ms

Caching Strategy

Response Caching

import { LRUCache } from 'lru-cache';

const cache = new LRUCache<string, any>({
  max: 1000,  # 1000: 1 second in ms
  ttl: 60000, // 1 minute  # 60000: 1 minute in ms
  updateAgeOnGet: true,
});

async function cachedFireCrawlRequest<T>(
  key: string,
  fetcher: () => Promise<T>,
  ttl?: number
): Promise<T> {
  const cached = cache.get(key);
  if (cached) return cached as T;

  const result = await fetcher();
  cache.set(key, result, { ttl });
  return result;
}

Redis Caching (Distributed)

import Redis from 'ioredis';

const redis = new Redis(process.env.REDIS_URL);

async function cachedWithRedis<T>(
  key: string,
  fetcher: () => Promise<T>,
  ttlSeconds = 60
): Promise<T> {
  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const result = await fetcher();
  await redis.setex(key, ttlSeconds, JSON.stringify(result));
  return result;
}

Request Batching

import DataLoader from 'dataloader';

const firecrawlLoader = new DataLoader<string, any>(
  async (ids) => {
    // Batch fetch from FireCrawl
    const results = await firecrawlClient.batchGet(ids);
    return ids.map(id => results.find(r => r.id === id) || null);
  },
  {
    maxBatchSize: 100,
    batchScheduleFn: callback => setTimeout(callback, 10),
  }
);

// Usage - automatically batched
const [item1, item2, item3] = await Promise.all([
  firecrawlLoader.load('id-1'),
  firecrawlLoader.load('id-2'),
  firecrawlLoader.load('id-3'),
]);

Connection Optimization

import { Agent } from 'https';

// Keep-alive connection pooling
const agent = new Agent({
  keepAlive: true,
  maxSockets: 10,
  maxFreeSockets: 5,
  timeout: 30000,  # 30000: 30 seconds in ms
});

const client = new FireCrawlClient({
  apiKey: process.env.FIRECRAWL_API_KEY!,
  httpAgent: agent,
});

Pagination Optimization

async function* paginatedFireCrawlList<T>(
  fetcher: (cursor?: string) => Promise<{ data: T[]; nextCursor?: string }>
): AsyncGenerator<T> {
  let cursor: string | undefined;

  do {
    const { data, nextCursor } = await fetcher(cursor);
    for (const item of data) {
      yield item;
    }
    cursor = nextCursor;
  } while (cursor);
}

// Usage
for await (const item of paginatedFireCrawlList(cursor =>
  firecrawlClient.list({ cursor, limit: 100 })
)) {
  await process(item);
}

Performance Monitoring

async function measuredFireCrawlCall<T>(
  operation: string,
  fn: () => Promise<T>
): Promise<T> {
  const start = performance.now();
  try {
    const result = await fn();
    const duration = performance.now() - start;
    console.log({ operation, duration, status: 'success' });
    return result;
  } catch (error) {
    const duration = performance.now() - start;
    console.error({ operation, duration, status: 'error', error });
    throw error;
  }
}

Instructions

Step 1: Establish Baseline

Measure current latency for critical FireCrawl operations.

Step 2: Implement Caching

Add response caching for frequently accessed data.

Step 3: Enable Batching

Use DataLoader or similar for automatic request batching.

Step 4: Optimize Connections

Configure connection pooling with keep-alive.

Output

  • Reduced API latency
  • Caching layer implemented
  • Request batching enabled
  • Connection pooling configured

Error Handling

Issue Cause Solution
Cache miss storm TTL expired Use stale-while-revalidate
Batch timeout Too many items Reduce batch size
Connection exhausted No pooling Configure max sockets
Memory pressure Cache too large Set max cache entries

Examples

Quick Performance Wrapper

const withPerformance = <T>(name: string, fn: () => Promise<T>) =>
  measuredFireCrawlCall(name, () =>
    cachedFireCrawlRequest(`cache:${name}`, fn)
  );

Resources

Next Steps

For cost optimization, see firecrawl-cost-tuning.

04 同仓库更多 Skills

micsapp
micsapp/micstec-skills

azure-apim-architecture

Analyzes and explains Azure API Management architecture decisions for enterprise API marketplace implementations using VNet Internal mode, Front Door, hybrid authentication, and multi-environment strategies. Use when discussing APIM component selection, network topology, cost optimization, or comparing alternatives like workspaces vs instances, VNet Internal vs External mode, or Front Door vs Application Gateway.

开发工程师后端与接口
★ 4
micsapp
micsapp/micstec-skills

apiops-deployment

Guides deployment of Azure API Management infrastructure using Infrastructure as Code (Bicep/Terraform), CI/CD pipelines (GitHub Actions/Azure DevOps), and APIOps workflows. Use when deploying APIM, creating pipelines, or implementing dev→test→prod promotion strategies.

开发工程师后端与接口运维与部署
★ 4
micsapp
micsapp/micstec-skills

apim-policy-authoring

Creates production-ready Azure API Management policy XML for authentication (OAuth 2.0, JWT validation, subscription keys), rate limiting, CORS configuration, error handling, and API transformations. Use when implementing API security, access control, or request/response processing logic.

后端与接口
★ 4
micsapp
micsapp/micstec-skills

api-security-review

Reviews Azure API Management configurations for security vulnerabilities, OWASP API Security Top 10 compliance, VNet Internal mode validation, Private Link verification, and Azure Security Benchmark alignment. Use when performing security audits, pre-deployment validation, or compliance reviews.

开发工程师后端与接口
★ 4
micsapp
micsapp/micstec-skills

jira-cli

Interact with Jira from the command line to create, list, view, edit, and transition issues, manage sprints and epics, and perform common Jira workflows. Use when the user asks about Jira tasks, tickets, issues, sprints, or needs to manage project work items.

★ 4
micsapp
micsapp/micstec-skills

calculator

Performs arbitrary-precision arithmetic calculations including addition, subtraction, multiplication, division, and exponents. Use when the user asks to calculate, compute, or evaluate math expressions, or when precise decimal arithmetic is needed to avoid floating-point errors.

★ 4