Skill UI

This comprehensive guide teaches you how to integrate and use the ElevenLabs Text-to-Speech (TTS) API. It provides multiple code examples (TypeScript, Python, cURL) for generating high-quality speech audio from text. Learn advanced features such as detailed voice parameter control, choosing optimal models (e.g., streaming vs. standard), and implementing low-latency streaming for real-time applications.

This guide provides a robust implementation for handling asynchronous webhooks from ElevenLabs. It covers the critical steps of receiving POST notifications (such as transcription completion, post-call audio, and failure events), performing secure HMAC-SHA256 signature verification, and routing the event data to specific processing handlers. Ideal for integrating ElevenLabs into conversational AI pipelines, ensuring data integrity and reliable background processing.

A comprehensive evaluation suite designed to benchmark the performance of Large Language Models (LLM) and Vision-Language Models (VLM) specifically for home security applications. It covers 143 diverse tests across 16 critical domains, including tool use, prompt injection resistance, contextual reasoning, alert triage, and detailed scene analysis, ensuring robustness for smart home AI systems.

This benchmark evaluates Vision-Language Models (VLMs) on detecting potential safety hazards within indoor environments. It uses static camera frames, simulating real-world fixed security camera monitoring. The test covers 40 scenarios across 5 critical categories, including fire/smoke, electrical risks, trips/falls, child safety, and falling objects, providing a rigorous measure of VLM's practical safety inspection capability.

Lambda is a compact, machine-native communication protocol specifically designed for agent-to-agent (A2A) messaging. It functions as a shared, unambiguous vocabulary built from 'atoms' (2-character codes), completely bypassing the need for human natural language interpretation. It is ideal for orchestrators, task delegation, and logging structured coordination signals (like heartbeats or state changes) in multi-agent systems. Crucially, Lambda is intended only for machine communication, not for user-facing dialogue.

A robust framework for building complex, long-horizon AI agents using LangGraph. It addresses common pitfalls in advanced agent design, such as unbounded state growth (Virtual FS cleanup) and subagent persona leakage (explicit message overriding). Ideal for tasks requiring multi-step planning, task delegation, and self-correction through reflection loops.

Implement robust human-in-the-loop (HITL) approval gates for sophisticated LangGraph workflows. This skill enables the graph to pause execution before critical, irreversible actions (like sending emails or calling tools). It manages complex state serialization, provides clear resume semantics using `Command(resume=...)`, and integrates with external UIs (e.g., Slack) to await human decision, ensuring safe and controlled workflow execution.

This is an all-in-one command-line tool for generating and editing images using the full Nano Banana model family. Users can select the optimal model—Gemini 3.1 Flash for balanced performance, Gemini 3 Pro for high-quality output, or Gemini 2.5 Flash for speed—to suit their needs. Key features include text-to-image generation, precise single image editing, and multi-image collage composition, making it versatile for creative and technical workflows.

A remote MCP server designed for AI agents to dynamically discover, inspect, and verify external tools, APIs, and services. It allows agents to search a curated index of AI-ready websites, check for machine-readable endpoints (like OpenAPI or MCP), and confirm if an endpoint responds correctly to JSON-RPC, enabling robust, dynamic agent workflow building.

Simulates a comprehensive, multi-round patent examiner review process. It analyzes patent claims and specifications against international standards (USPTO, CNIPA, EPO) to assess novelty, non-obviousness, claim clarity, and enablement. The tool provides detailed office actions, critical feedback, and iterative improvement rounds to maximize patentability.

This guide helps determine the optimal deployment strategy for Qdrant, a vector database. It compares four main options—Local Mode, Self-Hosted (Docker), Qdrant Cloud (Zero-Ops), and Qdrant EDGE—based on project requirements such as control needs, operational overhead, data residency, and required latency. Use it to decide whether to prototype, manage full infrastructure, or prioritize minimal latency.

A comprehensive guide and implementation pattern for handling common errors when working with the Runway AI platform. This skill provides Python SDK examples for tasks like image-to-video generation, along with structured solutions for API issues such as 'Unauthorized' (401) or 'Insufficient credits' (402), ensuring smooth and reliable creative AI workflows.