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Found 159 Skills
Organize research, discussions, and exploratory content into systematic knowledge documents, or collect and organize research information about companies/products. Use this skill when users request knowledge summarization, note organization, knowledge base document generation, or structuring discussion content into formal documents. It also applies to collecting and organizing research information about AI companies, startups, and products. Even if users don't explicitly mention "knowledge graph" or "knowledge base", this skill should be used for any workflow that involves sorting scattered information into systematic documents.
Spatial organization of knowledge in navigable directories
The foundational knowledge distillation pattern for building and maintaining an AI-powered Obsidian wiki. Based on Andrej Karpathy's LLM Wiki architecture. Use this skill whenever the user wants to understand the wiki pattern, set up a new knowledge base, or needs guidance on the three-layer architecture (raw sources → wiki → schema). Also use when discussing knowledge management strategy, wiki structure decisions, or how to organize distilled knowledge. This is the "theory" skill — other skills handle specific operations (ingesting, querying, linting).
dontbesilent Folder Knowledge Base. Transform users' existing local folders into a knowledge base that Agents can reliably search, archive, and maintain; build a minimal knowledge base when users have no materials, generate a knowledge base navigation when materials exist, and support subsequent functions such as adding new materials, searching for answers, identifying current versions, and checking the health status of the knowledge base. Use this whenever users mention phrases like "build a knowledge base", "my folder is the knowledge base", "let AI understand these files", "put materials into the knowledge base", "find things from the knowledge base", "which file is the latest version", "materials are too messy", "establish a Source of Truth". Users don't need to understand Source of Truth, RAG, or Agent configurations. Folder-based knowledge base for AI agents. Use whenever the user wants to build, populate, query, organize, audit, or connect a local folder as a knowledge base, including source-of-truth navigation and version resolution.
Use this skill when the user wants to repair or strengthen Obsidian wikilinks among existing canonical project notes, especially across papers, knowledge notes, experiments, results, and writing.
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
Two-tier memory system that makes Claude a true workplace collaborator. Decodes shorthand, acronyms, nicknames, and internal language so Claude understands requests like a colleague would. CLAUDE.md for working memory, memory/ directory for the full knowledge base.
Create a 'how does X work' documentation file for a codebase component or concept. Use $ARGUMENTS as the doc topic if provided.
Post-task review. Extract learnings, classify, write to memory layers, and reconcile GitHub issues.
Build a personal knowledge wiki from your notes, journals, and documents. LLM ingests data, synthesizes cross-linked Wikipedia-style articles, and serves a web UI.
Transforms knowledge sources into an Obsidian StudyVault. Two modes: (1) Document Mode — PDF/text/web sources → study notes with practice questions. (2) Codebase Mode — source code project → onboarding vault for new developers. Mode is auto-detected based on project markers in CWD.
Use when building a managed team skills library for a real stack. Map work to shelves, browse before curating, write meaningful `whyHere` notes, and create a starter pack once the first pass is solid.