Skill UI

This guide provides comprehensive strategies and code examples for managing and reducing API costs associated with large-scale usage of Lucidchart. It covers optimizing document exports through caching, batching operations, reducing excessive real-time collaboration events, and efficiently managing user seats to ensure cost-effective diagramming workflows.

This guide provides comprehensive strategies for optimizing API usage and managing costs when integrating with Miro. It covers credit monitoring, advanced techniques like caching, server-side filtering, batching, and subscribing to webhooks. By implementing these best practices, developers can drastically reduce API call volume, stay within rate limits, and ensure highly efficient and cost-effective application development.

This skill implements a comprehensive solution for managing Miro REST API rate limits. It incorporates a credit-based monitoring system, exponential backoff with jitter, and request queuing. This ensures reliable, high-throughput data integration by respecting Miro's usage quotas and handling API throttling (429 errors) gracefully.

A comprehensive guide providing production-ready, structured patterns for interacting with the Miro API. It covers best practices for both the high-level stateful client usage and the low-level REST API v2. Includes patterns for implementing robust Board Services (fetching, pagination) and Item Factories (creating various elements like sticky notes, shapes, and cards). Essential for developers building SaaS applications or complex automation workflows using Miro.

This skill provides comprehensive strategies to optimize resource usage and mitigate rate limits when integrating with the OneNote Graph API. It focuses on reducing the operational 'cost' of making API calls by implementing metadata caching (TTL), utilizing JSON batch requests, and performing delta synchronization instead of full list fetches. Essential for high-volume, stable OneNote enterprise integrations.

This skill provides a comprehensive guide and code examples for creating a complete OneNote structure (Notebook, Section, and Page) using the Microsoft Graph API. It specifically addresses the critical technical requirement that OneNote content must follow strict XHTML standards, detailing common HTML pitfalls (such as unclosed tags, unsupported attributes, and merge cell usage) that can lead to silent content corruption during API calls.

This skill provides advanced rate limit handling for the OneNote Graph API. It implements a token bucket algorithm and queue-based throttling mechanism to prevent hitting rate limits (429 errors). It correctly parses the 'Retry-After' header and manages both per-user and per-tenant usage quotas, ensuring stable, high-throughput integrations.

This skill uses the OCI Usage API and SDK to programmatically track spending across compartments, services, and shapes. It allows users to query granular cost data, set detailed budget alerts (e.g., 80%, 95%, forecast), and identify cost optimization opportunities like utilizing Always Free tiers or preemptible instances, ensuring proactive and precise cloud cost management.

Programmatically query Oracle Cloud Infrastructure (OCI) metrics using the Monitoring Query Language (MQL) and create monitoring alarms via the Python SDK. This skill bypasses the limitations of the OCI console query builder, allowing reliable retrieval of key infrastructure metrics such as CPU utilization, memory usage, network traffic, and disk I/O. Ideal for building robust dashboards, automating resource monitoring, and setting up complex alerting rules.

A comprehensive guide for diagnosing and reducing high memory consumption in Qdrant. This resource is crucial when dealing with reports of 'memory leak', 'out of memory', or excessive RAM growth. It details how Qdrant manages resident memory and OS page cache, and provides advanced techniques such as quantization, using float16/int8 data types, and strategically storing components on disk (like HNSW indexes or sparse vectors) to minimize the memory footprint and ensure stable, scalable operation.

This guide provides comprehensive guidelines for performing vertical scaling on Qdrant instances. Vertical scaling involves upgrading the computational resources (CPU, RAM, or disk) of existing nodes rather than adding new nodes. It is the recommended first step when single nodes experience resource exhaustion (e.g., RAM usage > 80%, CPU saturation). The guide covers sizing guidelines, best practices for cloud deployment, and clearly defines the thresholds when horizontal scaling becomes necessary.

This skill provides the comprehensive API integration pattern for managing corporate cards and expenses using the Ramp Developer API with OAuth2 authentication. It is designed for developers building workflows that require synchronization, management, or retrieval of company financial data, such as tracking card usage or reconciling corporate expenses.