Can I use this for local development?

Yes, the skill includes k6 load testing scripts that can be run locally to benchmark your FireCrawl implementation before full-scale deployment.

What is the FireCrawl Load & Scale skill?

It is a specialized Claude Code skill designed to help developers test and scale their FireCrawl web scraping integrations using k6 and Kubernetes.

Does this skill require Kubernetes?

While the auto-scaling features are optimized for Kubernetes HPA, the load testing, capacity planning, and connection pooling features can be used in any environment.

How do I trigger this skill in Claude Code?

Use natural language triggers like 'firecrawl load test', 'perform firecrawl benchmark', or 'configure firecrawl scaling' to activate the skill's capabilities.

What metrics are used for capacity planning?

The skill monitors key performance indicators including CPU utilization, memory usage, request queue depth, error rates, and P95 latency to provide data-driven scaling recommendations.

FireCrawl Load & Scale

Name: FireCrawl Load & Scale
Author: jeremylongshore

byjeremylongshore

•

982

Deployment & DevOps

Optimizes FireCrawl integrations through automated load testing, horizontal auto-scaling, and data-driven capacity planning.

About

The FireCrawl Load & Scale skill provides comprehensive tools for ensuring high-performance web crawling operations. It enables developers to execute sophisticated k6 load tests, configure Kubernetes Horizontal Pod Autoscalers (HPA) for dynamic traffic demands, and implement connection pooling to manage API throughput efficiently. By providing benchmark templates and capacity calculation logic, it helps teams move from reactive scaling to proactive resource management, ensuring FireCrawl implementations remain stable under varying loads and high-volume data extraction tasks.

Key Features

Connection pooling patterns for efficient API client management
Automated k6 load testing scripts with custom performance thresholds
Standardized performance benchmark reporting and documentation templates
Real-time capacity estimation and infrastructure headroom analysis
982 GitHub stars
Kubernetes HPA configuration for dynamic resource scaling

Use Cases

Calculating infrastructure requirements and costs for large-scale data extraction projects
Benchmarking FireCrawl performance before moving scraping workflows to production
Implementing auto-scaling for variable scraping workloads on Kubernetes clusters

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills firecrawl-load-scale

For use in Claude.ai and ChatGPT

Download Skill

GitHub