Skill UI

This skill provides advanced connection-discovery and semantic search across your personal Apple Notes. It moves beyond simple keyword matching to find related ideas, identify non-obvious 'bridges' between concepts, and synthesize comprehensive summaries of your thoughts. Ideal for knowledge workers looking to recall, analyze, or map their personal knowledge base.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

This skill enables the creation and maintenance of highly structured, configurable research wikis. It manages source provenance, compiling raw source materials into organized concept pages, index maps, and derived artifacts. Ideal for systematically documenting complex knowledge bases, such as research notes, product documentation, or domain studies, ensuring full traceability and consistency.

This skill provides a repeatable assessment for RAG systems, testing for critical vulnerabilities in vector stores and embedding models. It specifically addresses embedding inversion, cross-tenant data leakage, and knowledge-base poisoning, aligning with OWASP LLM08:2025. Use when performing authorized security audits of retrieval layers and multi-tenant isolation.

This comprehensive skill acts as a virtual Chief of Staff, guiding founders through a rigorous 12-phase interview process. It systematically gathers and structures every facet of a business—from foundation and strategy to legal and governance—into a compliant Open Knowledge Format (OKF) bundle. Ideal for creating comprehensive, machine-readable company documentation, internal wikis, or knowledge bases for AI agents.

Context Kit is an external framework designed to organize and manage personal, durable context data (like identity details, memories, and domain knowledge) into secure Markdown artifacts. It helps users set up robust knowledge bases for coding agents (e.g., Claude Code), guiding them on best practices for data privacy, local storage, and safe integration, while preventing sensitive data leaks.

This skill guides the creation of comprehensive, structured strategic documents (SSOT, life vision, principles) using a strict, iterative interview-style methodology. Instead of generating content, the AI asks one focused question at a time. The user provides the answer, and the AI patches the document incrementally, ensuring the user remains the primary author. It is ideal for deep reflection, strategic planning, and building authoritative knowledge bases.

A comprehensive tool for querying, storing, and managing complex knowledge across multiple agent sessions. AgentDB utilizes advanced techniques including semantic routing, hierarchical recall, causal graph construction, and context synthesis. Use this skill when your application requires robust, multi-faceted knowledge retrieval and reasoning based on structured and unstructured data. It provides a structured workflow for checking system health, starting sessions, storing knowledge in tiers (working, episodic, semantic), and searching learned patterns.

This skill helps developers structure and record critical architectural decisions (ADRs) made during coding sessions. It automatically detects moments of decision, capturing the context, alternatives considered, and the rationale (trade-offs and consequences). This maintains a living log that explains 'why' the code base was built the way it is, preventing knowledge loss and improving project maintainability.

An advanced system that analyzes coding sessions via hooks to extract atomic, confidence-scored behaviors called "instincts." It tracks patterns, allowing users to evolve these instincts into comprehensive skills, commands, or agents. V2.1 introduces project-scoped learning, preventing knowledge contamination between different codebases and improving development workflow efficiency.

This tool enables the creation and management of Dynamic Agentic Architecture (DAA) agents. Unlike static agents, DAA agents possess the ability to learn, adapt their internal behavior based on real-time performance metrics, and continuously evolve through interactions. It facilitates knowledge sharing among multiple agents, ensuring systemic, continuous improvement in complex AI systems. Ideal for scenarios requiring high adaptability and evolving intelligence.

This tool performs a deep, recursive, and parallel investigation, building a comprehensive graph-structured dossier around a specified seed entity. It expands outward across diverse sources, including web search, internal memory stores, codebases, and knowledge graphs. It captures all connected entities and the provenance of every claim, making it ideal for mapping the full context or relationship network of a subject.