Skill UI

This guide provides comprehensive, step-by-step instructions for installing and authenticating the Anthropic SDK. It covers setup for both Python and Node.js environments, detailing how to securely configure API keys using environment variables. Essential for developers starting new projects that integrate with Claude models.

A comprehensive guide for scaling Claude usage in high-throughput, enterprise-level applications. Learn four advanced strategies, including Message Batches for bulk processing, using p-limit for concurrency control, managing rate limit tier upgrades, and selecting the optimal model (e.g., Haiku) to balance speed and quality.

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 covers advanced usage of the Anthropic Messages API. Learn how to implement real-time streaming responses, utilize system prompts for persona control, process visual inputs (Vision), and enforce structured data output (JSON). This is essential for building sophisticated, robust, and multi-modal Claude-powered applications.

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.

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.

A comprehensive guide for diagnosing and fixing common errors encountered when integrating with the Anthropic API (Claude). It covers critical issues such as authentication failures (401), rate limiting (429), server overload (529), invalid requests, and context window limits. Includes practical code solutions and best practices for robust API integration.

This skill provides the comprehensive workflow for interacting with the Anthropic Messages API. It covers advanced features including streaming responses, multimodal vision input, generating structured JSON output using system prompts, and managing multi-turn conversations. It redirects users to the current, primary guide for all Claude API patterns.

This guide demonstrates how to build advanced AI agents using Anthropic's Tool Use (Function Calling) feature. It allows Claude to dynamically determine when external actions are needed, such as querying databases, calling APIs, or reading files. The pattern involves sending the user query, receiving a `tool_use` request, executing the corresponding function in your code, and submitting the result back to Claude for a final, coherent response. Essential for building multi-step, agentic workflows.

A logging wrapper designed to instrument and monitor calls to the Claude API. It automatically tracks critical metrics including token usage, API latency, estimated cost, and error details. Essential for implementing robust observability patterns and setting up proactive alerts in production environments.

This guide details how to implement robust content safety guardrails for applications powered by Claude. It covers essential techniques such as system prompt hardening, input validation to detect injection patterns and length limits, and output validation to prevent system prompt leakage. It ensures compliance with Anthropic's policies, making the AI integration secure and reliable.