Skill UI

A conversational onboarding skill designed to deeply understand the user and define the core identity of an AI partner. Through adaptive, multi-phase dialogue, it extracts key behavioral traits, motivations, and relationship dynamics, culminating in the generation of a comprehensive SOUL.md file that governs the AI's personality and interaction style. Use this skill when setting up, personalizing, or updating your AI agent.

This guide details the OpenViking long-term memory plugin, which enhances conversational AI by automatically capturing key facts and preferences from past interactions. It utilizes auto-capture modes (semantic or keyword) to store memories and automatically recalls relevant context before generating a response, ensuring continuity and personalization across long conversations. Provides tools for retrieval, manual storage, and memory deletion.

This skill transforms written content, such as articles and reports, into engaging, two-host conversational podcast audio. It first structures the content into a detailed JSON script (dialogue format) and then uses advanced Text-to-Speech synthesis to generate the final MP3 file. Supports both English and Chinese languages, making content accessible for audio-only listening.

This skill provides comprehensive tools to download, export, and deeply inspect existing Arize traces and spans. It is essential for understanding the full execution flow of complex LLM applications, debugging runtime errors, and performing root-cause analysis. Users can retrieve detailed data filtered by Trace ID, Span ID, or Session ID, enabling thorough analysis of conversational or multi-step agent behaviors.

This skill is designed to manage complex, multi-step tasks by coordinating the efforts of multiple specialized AI agents. It provides structured methods for listing available agents, initiating real-time conversations, submitting complex background tasks (such as data analysis or report generation), tracking task status, and maintaining conversational context using session IDs. It is essential when a core task requires diverse expert knowledge or sequential collaboration.

This guide provides comprehensive techniques for optimizing ElevenLabs Text-to-Speech (TTS) performance. Learn how to reduce latency and maximize throughput by strategically selecting models (e.g., Flash vs. v3), implementing streaming endpoints (HTTP or WebSocket), and choosing optimal audio formats. It is essential for real-time conversational AI, IVR systems, and high-volume content generation.

Manage a personal boycott list conversationally. Users tell the agent which brands they want to avoid and provide specific reasons. The system syncs this data to a local server and powers a Chrome extension. This extension monitors visited pages and alerts the user with a prominent warning banner whenever they land on a site from a boycotted brand, displaying their own personal reason for the boycott.

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.

This workflow demonstrates the core capabilities of the Glean Client API, allowing users to build comprehensive knowledge assistants. It covers advanced full-text search with filters and facets, implements AI-powered chat for contextual Q&A, and provides autocomplete suggestions. Ideal for integrating deep search and conversational AI into enterprise applications.

This skill facilitates an interactive Quality Assurance (QA) session. Users can conversationally describe encountered bugs or issues. The agent clarifies the problem, explores the codebase for context and domain language, and then meticulously files durable GitHub issues. It supports both single-issue reports and breaking down complex problems into multiple, independently verifiable tickets, ensuring developers receive actionable, high-quality reports written from the user's perspective.

This tool extracts and formalizes the core business terminology (Ubiquitous Language) from a conversational context. It generates a structured glossary, identifies ambiguities, resolves conflicting terms, and proposes canonical names. It is essential for building consistent and unambiguous domain models, particularly when following Domain-Driven Design (DDD).

A comprehensive, expert-level guideline for building Agentic User Interfaces (UIs). This system emphasizes conversational interactions, clear outcomes, and minimal user controls, allowing users to delegate complex tasks to AI. It provides structured rules covering color tokens, typography, accessibility (WCAG 2.2 AA), and component anatomy for professional developers and designers.