Skill UI

This skill is designed to facilitate communication and collaboration between different AI agents. Use it when you need to consult an expert agent, request a plan, seek a review, or continue a context-aware conversation with a specialized agent. It handles both real-time foreground chat and asynchronous background task submission, ensuring robust multi-agent workflows.

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.

Self-hosted open-source alternative to NotebookLM for organizing research, ingesting diverse sources, generating AI notes, running context-aware chats, performing vector search, producing multi-speaker podcasts, and automating workflows via a REST API.

A comprehensive guide for building applications with Claude, ensuring responsible data handling. This skill covers critical patterns such as PII redaction (stripping sensitive data like emails, phone numbers, and card numbers), optimizing the 200K token context window through conversation trimming, and implementing best practices for data retention and privacy compliance when interacting with the Anthropic API.

A persistent memory kit designed for Claude AI agents. It maintains deep context across multiple sessions and projects using a two-layer architecture (hot cache and knowledge wiki). Features include safety hooks, multi-project context isolation, and a /close-day command for daily synthesis, ensuring agents remember complex information and continuously learn.

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.

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 assistant functions as a professional prompt engineer, specializing in generating highly optimized, production-ready prompts for diverse AI platforms. It analyzes user intent and technical requirements across nine dimensions (Task, Context, Format, etc.), then tailors the prompt structure, constraints, and tone specifically for the target model (e.g., GPT-5.x, Claude, Gemini, Midjourney). Use it when you need to convert a vague idea into a structured, high-performing command for any large language model or generative AI tool.

This skill provides a structured framework for capturing, organizing, and maintaining persistent facts about the user. By segmenting facts into topic-specific files (e.g., coding preferences, tech stack, goals), it creates a reliable, objective knowledge base. This structure is crucial for AI agents and applications to achieve highly personalized interactions and provide accurate context.

This guide provides detailed instructions for optimizing cost and implementing voice-to-text API integrations using Wispr Flow. It covers best practices for WebSocket streaming, REST API usage, context awareness (like programming code), and robust error handling, helping developers build advanced voice-powered applications.