Skill UI

Master the art of developing robust and scalable Python applications that interface with Microsoft Dataverse. This skill covers implementing enterprise-grade best practices, including comprehensive error handling using DataverseError hierarchy, advanced retry logic with exponential backoff, and optimizing API calls using OData standards (filtering, selecting, and expanding). It ensures code is clean, maintainable, and production-ready.

Analyzes and generates a self-contained, explorable HTML report detailing usage metrics for Claude Code sessions. It tracks token consumption (input/output), subagent usage, skill calls, and cache efficiency across specified time ranges. This tool helps developers visualize resource waste and pinpoint areas for workflow optimization, ensuring cost-effective and efficient AI development cycles.

EverOS OpenClaw Plugin integrates persistent, long-term memory capabilities into OpenClaw using the ContextEngine API. It goes beyond simple memory slots by automatically recalling relevant past context before a reply and saving new conversation content after a turn. This allows users to chat naturally while ensuring context, preferences, and key details persist across multiple sessions, eliminating the need for manual memory calls.

A comprehensive guide and toolkit for optimizing and monitoring consumption-based costs across the Adobe Creative Cloud ecosystem. It provides strategies and code snippets for tracking usage (credits, transactions) for Firefly, PDF Services, Photoshop, and Lightroom APIs. Use this when implementing usage monitoring, managing billing alerts, or reducing operational expenses related to Adobe API calls.

This comprehensive guide details advanced strategies for optimizing performance when interacting with blockchain data using the Alchemy SDK. Techniques covered include implementing TTL-based caching for data freshness, achieving parallel multi-chain fetches, utilizing batch API calls (e.g., NFT metadata) to reduce Compute Unit (CU) costs, and adopting WebSockets for real-time event subscriptions. Essential for scaling robust, low-latency dApps.

This skill provides actionable strategies and code patterns to significantly reduce Anima API costs. It focuses on optimizing usage through generation caching, detecting component changes for incremental generation, and implementing smart policies to minimize unnecessary API calls. Ideal for managing large-scale design-to-code workflows and controlling API budget.

This skill provides comprehensive strategies for optimizing API usage with BambooHR. It helps developers reduce unnecessary API calls, preventing rate limiting errors (503s) and ensuring stable system synchronization. Learn critical best practices such as replacing inefficient polling with webhooks, implementing robust data caching, and precisely requesting only the necessary fields.

A comprehensive guide for debugging complex Claude integration issues beyond basic error handling. It covers advanced patterns such as managing inconsistent outputs (temperature control), validating tool use calls, recovering from streaming connection drops, handling max_tokens truncation, and correctly processing image/vision inputs. Essential for building robust, production-grade AI applications with Anthropic's API.

A comprehensive guide for managing Anthropic API rate limits (RPM, TPM). Learn how to interpret rate limit headers, implement robust backoff strategies (exponential backoff with jitter), and optimize throughput using techniques like message batching and prompt caching to ensure reliable, high-volume API calls.

This guide provides advanced strategies for optimizing API usage and managing costs when integrating with ClickUp. It covers techniques such as aggressive caching of workspace structures, efficient pagination, batching multiple updates into single calls, and switching from constant polling to webhook-based event handling. Learning these methods helps developers stay within rate limits and maximize API efficiency.

A robust utility for managing API calls to ElevenLabs, handling complex rate limiting, concurrency queuing, and quota monitoring. It implements plan-aware concurrency controls (managing 'too_many_concurrent_requests') and exponential backoff strategies for system overloads ('system_busy'). This is essential for building reliable, high-throughput Text-to-Speech applications.

This setup provides a local development loop for integrating and testing Fathom API functionalities. It utilizes mock meeting and transcript data, making it ideal for building meeting analytics tools, simulating webhook handlers, or iterating on complex transcript processing pipelines without requiring live API calls. It ensures a robust environment for isolated development testing.