Skill UI

This comprehensive skill provides full programmatic control over the entire work order lifecycle within the MaintainX platform. Users can create new work orders with detailed metadata, programmatically transition their status (Open, In Progress, On Hold, Completed), query existing tasks, and attach documentation or comments. It is ideal for automating complex maintenance operations and ensuring end-to-end operational visibility.

A comprehensive guide to minimizing API usage costs by implementing advanced integration patterns. Learn to reduce request volume through response caching with TTL, replacing expensive polling with webhook-driven sync, and utilizing smart polling with change detection filters. Also covers usage tracking and request deduplication for highly efficient system architecture.

This guide provides advanced techniques for optimizing API integration performance with MaintainX. It covers essential concepts such as connection pooling, implementing multi-level caching (L1/L2 using Redis), batch data loading via DataLoaders, efficient cursor-based pagination, and request deduplication. Use this skill when optimizing slow API responses or improving overall system data throughput.

This guide teaches comprehensive security hardening for API integrations. Learn best practices for credential management (using environment variables/secret managers), implementing git hooks to prevent secret leaks, robust input validation (using Zod), structured audit logging, and mandatory key rotation procedures, ensuring system compliance and operational security.

Automate Make (Integromat) workflows via Rube MCP by retrieving operations, language, and timezone enums, ensuring schemas are current before each tool call.

Mamba is a selective state-space model architecture delivering O(n) inference for million-token sequences, offering hardware-aware Mamba-1 and Mamba-2 variants that beat Transformers on speed without KV cache overhead.

A comprehensive guide to implementing robust, multi-layered API response caching using distributed stores like Redis and Memcached, alongside CDN integration. Learn advanced strategies such as tag-based cache invalidation, read-through/write-through patterns, TTL management, and serving stale-while-revalidate content to drastically boost application performance and scalability.

Enables Claude to orchestrate isolated test environments using Docker Compose, Testcontainers, and environment variables, ensuring consistent setups for database, cache, and message-queue based testing across software projects.

A comprehensive guide for achieving compliance with the EU MDR 2017/745. It covers crucial aspects including medical device classification (Annex VIII), developing technical documentation (Annex II/III), planning clinical evaluation (CER), and establishing post-market surveillance (PMS/PSUR) systems. Ideal for regulatory specialists preparing for Notified Body audits or needing to gap-check technical files.

Automated memcached configuration assistant that provides best-practice guidance and production-ready snippets for caching, database, messaging, and microservices patterns in backend services.

This guide provides advanced techniques for optimizing Mistral AI API usage, focusing on latency reduction and throughput maximization. Learn to implement robust caching strategies, utilize streaming responses (SSE), select the optimal model for specific use cases (e.g., Mistral Small for chat, Codestral for code), manage concurrent requests using rate limiting, and efficiently use the Batch API. Essential for building high-performance, production-grade AI applications.

This guide provides a production-ready, layered architecture pattern for integrating Mistral AI into TypeScript/Node.js projects. It implements best practices including singleton client management, Zod-validated configuration, custom error handling, caching mechanisms, and robust service layer design (e.g., RAG pipelines). Use this when setting up new Mistral AI applications or needing standardized, reliable project structure.