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 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.

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.

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.

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.

This skill provides a comprehensive guide for integrating Anthropic Claude APIs into robust CI/CD pipelines. It includes mock-based unit tests for fast, reliable validation, as well as live prompt regression tests for ensuring output consistency on the main branch. Ideal for developers maintaining automated, Claude-powered features.

A comprehensive reference guide for diagnosing and fixing common Anthropic Claude API errors, categorized by HTTP status codes (400, 429, 500, etc.). Includes specific error JSON patterns, root causes (e.g., role alternation, rate limits), suggested fixes, and code examples in Bash and Python for effective troubleshooting.

This tool collects comprehensive diagnostic evidence for troubleshooting Anthropic Claude API issues. It gathers critical data such as request IDs, rate limit headers, SDK versions, and connection details. It is essential for generating accurate support tickets or diagnosing persistent API failures.