Skill UI

A comprehensive TypeScript SDK for integrating Azure AI Translator services. It provides robust clients for both real-time text translation (including language detection, transliteration) and large-scale document translation. Users can translate single documents or manage complex batch translation jobs using REST-style API calls, making multilingual support easy to integrate into applications.

Track and improve production LLMs with Langfuse observability: trace API calls, manage prompts, score evaluations, integrate with LangChain/LlamaIndex/OpenAI, and keep dashboards on cost, latency, and quality.

Practical guide to integrating Claude models: covers API client usage, streaming responses, tool calls, RAG pipelines, document chunking, cost-aware model selection, and anti-pattern warnings for efficient LLM workflows.

This skill provides architectural patterns and implementation guides for developing advanced voice agents and automating phone calls using the Retell AI platform. It covers SDK integration, API best practices, and troubleshooting common telephony errors (like 401/429), enabling developers to build robust, real-world voice interaction systems.

This comprehensive guide demonstrates how to build and test a voice agent using the Retell AI SDK in TypeScript. It walks through configuring the underlying LLM with a custom persona, creating the voice agent instance, and finally initiating both outbound phone calls and web calls through the API. This is essential for integrating AI-powered voice communication into customer service platforms, call centers, or telephony automation systems.

This skill provides deep dive implementation patterns for migrating and utilizing Retell AI. It focuses on building sophisticated voice agents and automating phone call interactions using the official SDK. Users will learn how to manage agents, handle API calls, and implement robust error handling for complex telephony applications, making it ideal for building automated call centers or interactive voice systems.

This skill provides implementation patterns for achieving observability in AI voice agents and telephony platforms built with Retell AI. It guides users on how to monitor the performance, status, and interactions of automated voice agents and phone calls. It also includes essential guidance on common API error handling (e.g., 401 Unauthorized, 429 Rate Limited), ensuring robust and reliable system operation.

Orchestrates Serpapi searches through Composio's Rube MCP by discovering current tool schemas, validating the connection, and executing schema-compliant calls with session reuse and explicit memory placeholders to keep automation workflows reliable.

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 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 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 demonstrates how to implement tool use (function calling) with Claude's Messages API. It covers defining structured tools using JSON Schema, handling tool calls, executing the corresponding code, and feeding the results back to create sophisticated, multi-step AI agents and complex workflows.