Skill UI

This guide teaches developers how to implement robust, event-driven architecture patterns with the Anthropic Claude API. It covers two key methods: Server-Sent Events (SSE) for real-time streaming responses, and the Message Batches API for high-volume, asynchronous bulk processing. Use this when building real-time chat features or processing large datasets offline.

A comprehensive guide to minimizing expenses when utilizing the Anthropic Claude API. Learn advanced strategies including right-sizing models (Haiku, Sonnet, Opus), prompt caching (up to 90% savings), message batching, and effective token reduction techniques. Essential for building cost-efficient AI applications.

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.

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.

A comprehensive guide providing minimal working examples for core Cohere API v2 endpoints, including Chat completion, text embedding, and search reranking. This resource details basic setup, usage patterns, and includes runnable code examples in both TypeScript and Python, making it perfect for new AI integrations or learning advanced LLM functionality.

A comprehensive security auditing framework designed to systematically detect sensitive information disclosure from Large Language Models (LLMs). It uses multi-phase, escalating dialogue probes to test for leaks such as system prompts, API keys, PII, and internal configurations. Essential for red teaming and rigorous model security assessment.

Implement professional text-to-speech generation and advanced voice cloning using the ElevenLabs API. This comprehensive workflow supports standard text-to-speech conversion, advanced voice customization (stability, similarity boost), and instant voice cloning from audio samples. It also includes WebSocket streaming for real-time applications like chatbots or live narration, making it ideal for building sophisticated, high-quality audio features.

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.

A comprehensive guide for setting up and authenticating access to the Fathom AI API. This skill walks users through generating API keys, configuring environment variables, and testing connectivity to retrieve meeting transcripts, summaries, and action items. Essential for integrating Fathom's meeting intelligence features into custom applications.

This skill creates and synchronizes prompt-based AI agents directly into Azure AI Foundry using the Agent Service REST API. By defining agents in a local JSON manifest, the skill registers them server-side, making them instantly available for evaluation and invocation within the Foundry ecosystem. It is essential for deploying, updating, or managing AI agents at scale within the Azure cloud environment.

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.