Skill UI

This guide provides a deep dive into migrating applications from OpenAI's GPT models to Anthropic's Claude API. It covers crucial API differences, including endpoint changes, response structure updates, handling the system prompt, tool use restructuring, and necessary SDK code swaps (e.g., TypeScript examples). Essential resource for developers transitioning AI backends.

This guide outlines advanced strategies to optimize latency and throughput when integrating Anthropic's Claude API. Learn critical techniques such as streaming responses, prompt caching, model selection (Haiku, Sonnet, Opus), and request parallelization, ensuring your applications provide a low-latency, high-performance user experience.

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 comprehensive guide details the full plugin architecture for extending Claude Code. Learn how to build various extension points, including auto-activating skills, slash commands, specialized agents, and Model Context Protocol (MCP) servers. It serves as the definitive reference for integrating custom tools and workflows into the Claude ecosystem.

A comprehensive guide for developers on upgrading the Anthropic SDK versions and migrating between different Claude model generations. It covers best practices for version checking, reviewing breaking changes, updating model IDs across the codebase, running output comparison tests, and implementing gradual rollouts using environment variables to ensure stable deployment.

Automate the testing and validation of Clari export pipelines within a Continuous Integration/Continuous Deployment (CI/CD) environment. This tool helps developers ensure API connectivity, validate export schemas, and systematically test the reliability of Clari integrations, preventing deployment issues before they reach production.

This tool gathers comprehensive diagnostic information from the Clari API, including connectivity status, recent forecast lists, job history, and environment details. It is essential for users preparing support tickets, debugging integration issues, or providing comprehensive samples to technical support teams. All sensitive data is automatically redacted.

This guide provides advanced methods to significantly boost Clari API performance and data pipeline efficiency. It covers parallelizing multi-period data exports using Python's concurrency features, implementing a robust local caching mechanism with Time-To-Live (TTL), and optimizing data warehouse loading using SQL MERGE statements. Use this when facing slow exports, high API call volume, or requiring fast data synchronization in multi-forecast environments.

This skill provides robust mechanisms to interact with the Clari API, specifically designed to handle rate limiting (HTTP 429 errors) and manage asynchronous bulk export jobs. It implements exponential backoff and sequential scheduling, ensuring reliable data retrieval and forecasting exports without hitting API limits. Ideal for automated data pipelines and background job processing.

A collection of production-ready client implementation patterns for interacting with the Clari v4 API, provided in both Python and TypeScript. This guide covers essential functionalities like listing and exporting forecast data, implementing job polling, and managing complex data transformation pipelines, ensuring reliable and reusable integration for development teams.

A comprehensive guide on deploying applications connected to ClickHouse Cloud across various modern cloud environments, including Vercel, Fly.io, and Google Cloud Run. This guide covers best practices for connection pooling, secure secret management, implementing health checks, and ensuring graceful shutdowns in serverless and containerized setups.

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.