Skill UI

This guide provides advanced techniques to boost Framer API performance. It covers critical optimization areas including batch CMS syncing to prevent timeouts, memoizing expensive React components for better render performance, establishing persistent WebSocket connections, and optimizing image URLs before CMS synchronization. Use this when aiming to improve overall speed and stability of Framer-integrated applications.

This skill guides the setup and configuration of the CAST AI Workload Autoscaler, enabling dynamic right-sizing of pod resource requests (CPU and Memory). It automatically adjusts resources based on actual usage, significantly reducing cloud over-provisioning costs. Use this guide to implement workload scaling policies, configure resource limits via Kubernetes annotations, and monitor scaling events in Kubernetes environments.

This skill provides comprehensive guidance on optimizing operational costs on the Apify platform. It covers analyzing Compute Units (CU) usage, managing proxy consumption (residential vs. datacenter), and optimizing scraping logic (memory, concurrency) to ensure efficient and cost-effective web scraping workflows.

This advanced tutor covers a wide range of university-level STEM subjects, including Computer Science, AI/ML, Physics, Chemistry, and Engineering. It moves beyond rote memorization, focusing instead on developing deep conceptual understanding and transferable problem-solving skills. The methodology emphasizes Socratic questioning, first principles reasoning, and diagnosing the root cause of knowledge gaps across disciplines.

This comprehensive guide details how to optimize Apify Actors for maximum efficiency, cost-effectiveness, and reliability. Learn to select the appropriate crawler (e.g., Cheerio, Playwright), tune concurrency limits, manage memory consumption, and implement robust proxy rotation strategies for diverse web scraping workloads, ensuring your scraping tasks are fast and stable.

This skill provides advanced strategies for optimizing Canva Connect API performance. It covers implementing robust caching mechanisms (in-memory and Redis) to reduce redundant calls, handling pagination using continuation tokens, and implementing smart polling with progressive backoff for asynchronous operations like exports. It also details connection pooling and concurrency management to maximize request throughput and minimize latency for stable Canva integrations.

This guide provides production-ready patterns for using the @clickhouse/client library in Node.js. It covers critical, real-world scenarios such as safe typed queries, streaming large data inserts (with backpressure handling), robust batch operations with retries, and streaming SELECT queries for low memory consumption. It also includes best practices for comprehensive error handling and connection lifecycle management, ensuring stable and scalable ClickHouse integrations for data pipelines.

This skill provides comprehensive observability for CoreWeave's GPU-intensive workloads running on Kubernetes. It monitors critical operational metrics, including GPU utilization, memory usage, inference latency (p99), and job completion rates. Use it for setting up DCGM metrics dashboards, configuring proactive alerts for underutilization or Out-Of-Memory (OOM) conditions, and ensuring high reliability for AI/ML deployments.

This skill converts complex technical descriptions, such as system architectures, data flow diagrams, flowcharts, and sequence diagrams, into professional, production-quality SVG diagrams. It supports various technical models, including Agent and Memory architectures, and exports the final output as high-resolution PNG files for seamless documentation and presentation use.

A comprehensive guide for configuring and managing Role-Based Access Control (RBAC) in Grammarly Enterprise deployments. This covers role hierarchies (Org Admin, Team Admin, Member, Guest), implementing secure API access, auditing user permissions, and maintaining compliance standards like HIPAA and SOC 2.

A comprehensive guide to ensuring robust state management for LangGraph agents. This skill addresses common checkpointing pitfalls (like missing thread_id or non-JSON serializable state) and details best practices for implementing reliable state persistence using MemorySaver or PostgresSaver. It covers thread discipline, schema migration, and time-travel debugging for production-ready applications.

A tool designed for persistent context management within AI coding sessions. Memory Kit solves the problem of context loss that occurs during compaction or session restarts by saving, loading, updating, and sharing critical session state to a dedicated `MEMORY.md` file. Key functions include creating snapshots of goals and decisions, syncing context across team members via Git, and auditing/pruning stale entries, ensuring continuous workflow and knowledge retention.