Skill UI

This tool accesses a persistent FTS5 knowledge base containing previously indexed project documentation, local content, and session memory. Instead of feeding entire raw sources into the conversation context, it allows users to perform targeted, efficient searches using specific queries and source scoping. This is ideal for quickly retrieving technical details, project specifications, or historical context without lengthy re-reading.

Designed for complex troubleshooting in home or small-team environments. This meta-skill orchestrates the entire process, guiding users through symptom intake, environment capture, external knowledge lookup, and generating a safe, step-by-step, and reversible repair plan for issues involving networks, Docker, Git, printers, and more.

This meta-skill provides a complete pipeline to bootstrap a domain knowledge base from any single seed input (URL, PDF, Git repository, or free text). It automatically classifies the source type, ingests the content using a multi-search engine, persists the summary to memory, and finally generates a structured XLSX index file, making the information immediately searchable and usable.

A comprehensive workflow designed to convert unstructured conversational data, meeting notes, and ad-hoc decisions into highly structured, linkable entries within Notion. This tool ensures that all captured knowledge—whether an FAQ, a 'how-to' guide, or a formal decision log—is properly documented, categorized, and linked to maintain a cohesive, searchable knowledge base for easy reuse across teams.

SkillOpt-Sleep provides a mechanism for autonomous agent self-improvement. By simulating a 'sleep' or 'dream' cycle, it harvests past interaction sessions, mines recurring tasks, and replays them through the designated backend. It consolidates learned knowledge into persistent memory and skills, ensuring that only strictly validated improvements are adopted via a held-out gate, simulating long-term competence gain from short-term experience. Ideal for scheduled, background optimization.

This skill provides comprehensive knowledge of the Power BI Enhanced Report (PBIR) JSON schema. It details the structured metadata for report components, including visuals, pages, themes, bookmarks, and complex formatting rules. Users learn how to read and manipulate the underlying PBIR JSON to understand how Power BI reports are built and customized, adhering to strict technical guidelines and operational best practices.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.

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 facilitates structured, bidirectional reading and knowledge synthesis for academic texts, theories, and articles. It forces users to first capture the source material's original intent, before critically mapping its relationships, conflicts, and absorptions against the CrossFrame framework. It ensures structured output with clear source boundaries, making it ideal for deep learning and scholarly work.

This skill generates a formal Architecture Decision Record (ADR) following industry-standard formats. It guides users through documenting the full rationale behind significant technical choices, ensuring that the context, alternatives considered, chosen option, and resulting trade-offs are all captured. Ideal for maintaining architectural integrity and knowledge transfer within engineering teams.

This skill guides users through structured, adaptive learning experiences for any topic. It diagnoses the user's current knowledge level and goal to create a personalized study path. It utilizes techniques like worked examples, retrieval questions, and spaced repetition to ensure deep understanding, making it ideal for self-study, skill acquisition, or subject review.