How does this skill improve my web scraping project?

It provides a proven, layered architecture that separates concerns—such as caching, error handling, and business logic—making your code easier to test, debug, and scale.

FireCrawl is a specialized API that crawls websites and converts their content into clean, LLM-ready markdown or structured data.

Is caching handled automatically?

The architecture includes a dedicated service layer for caching (e.g., using Redis) to reduce redundant API calls and improve response times.

Does this architecture include error handling?

Yes, it implements a custom error boundary designed to transform SDK-level errors into actionable application errors with built-in retry logic.

Can I use this skill with existing TypeScript projects?

Absolutely. While it's great for new setups, the skill also provides guidance on refactoring existing implementations into the recommended reference structure.

FireCrawl Reference Architecture

Name: FireCrawl Reference Architecture
Author: jeremylongshore

byjeremylongshore

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1,031

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Web Scraping y Recopilación de Datos

Implements production-ready project structures and architectural patterns for robust FireCrawl-based web scraping applications.

The FireCrawl Reference Architecture skill provides a standardized, layered blueprint for building scalable and maintainable data extraction services. It guides developers through implementing a TypeScript-based project layout that includes singleton client wrappers, robust error boundaries, caching layers, and health monitoring. By following these industry best practices, you can ensure your FireCrawl integrations are resilient, observable, and easy to scale across multiple environments.

Características Principales

01Multi-environment configuration management patterns

02Custom error boundaries for enhanced API resilience

03Standardized TypeScript project layout for scraping services

041,031 GitHub stars

05Automated health check endpoint configuration

06Singleton client wrapper with built-in caching and monitoring

Casos de Uso

01Establishing team-wide architecture standards for data extraction projects

02Designing a new enterprise-grade web scraping service from scratch

03Refactoring existing FireCrawl code to improve maintainability and performance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills firecrawl-reference-architecture

For use in Claude.ai and ChatGPT

Download Skill

Características Principales

01Multi-environment configuration management patterns

02Custom error boundaries for enhanced API resilience

03Standardized TypeScript project layout for scraping services

041,031 GitHub stars

05Automated health check endpoint configuration

06Singleton client wrapper with built-in caching and monitoring

Casos de Uso

01Establishing team-wide architecture standards for data extraction projects

02Designing a new enterprise-grade web scraping service from scratch

03Refactoring existing FireCrawl code to improve maintainability and performance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills firecrawl-reference-architecture

For use in Claude.ai and ChatGPT

Download Skill