Does this skill help with API rate limiting?

Yes, by implementing caching, deduplication, and batch loading, you significantly reduce the total number of requests sent to the MaintainX API, preventing rate limit triggers.

Is the pagination logic memory-efficient for large datasets?

Absolutely. The skill provides stream-based pagination patterns that allow you to process large datasets one item at a time without loading everything into memory.

How does this skill improve MaintainX API speed?

It implements response caching, deduplicates redundant requests, and utilizes connection pooling to reduce network overhead, resulting in significantly faster response times.

Do I need Redis to use this performance skill?

While Redis is recommended for distributed environments as shown in the examples, the caching logic can be easily adapted for in-memory storage if needed.

MaintainX Performance Tuning

Name: MaintainX Performance Tuning
Author: jeremylongshore

byjeremylongshore

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1,243

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API Development

Optimizes MaintainX API integrations through advanced caching, connection pooling, and efficient data fetching patterns.

This skill provides a comprehensive toolkit for developers integrating with the MaintainX API who need to achieve high-performance data throughput and low latency. It automates the implementation of production-grade patterns such as Redis-based response caching, HTTP connection pooling with keep-alive, memory-efficient stream pagination, and request deduplication. By applying these optimizations, developers can reduce API response times, avoid rate limits, and ensure their maintenance management workflows scale efficiently even when handling thousands of work orders and assets.

Key Features

01Performance monitoring and automated metric collection

02Redis-based response caching with pattern-based invalidation

03Memory-efficient stream-based and prefetch pagination

04Optimized HTTP connection pooling using keep-alive agents

05Request deduplication and batch loading via DataLoader

061,243 GitHub stars

Use Cases

01Managing bulk data synchronization without exceeding API rate limits

02Reducing latency in real-time dashboards displaying MaintainX work orders

03Optimizing backend performance for high-concurrency maintenance applications

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills maintainx-performance-tuning

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01Performance monitoring and automated metric collection

02Redis-based response caching with pattern-based invalidation

03Memory-efficient stream-based and prefetch pagination

04Optimized HTTP connection pooling using keep-alive agents

05Request deduplication and batch loading via DataLoader

061,243 GitHub stars

Use Cases

01Managing bulk data synchronization without exceeding API rate limits

02Reducing latency in real-time dashboards displaying MaintainX work orders

03Optimizing backend performance for high-concurrency maintenance applications

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills maintainx-performance-tuning

For use in Claude.ai and ChatGPT

Download Skill