Maintain a markdown knowledge base with interlinked topics and an index.
npx skills add https://github.com/SethGammon/Citadel --skill wiki-sethgammon
Please help me install this Agent Skill. Skill: wiki Source: https://github.com/SethGammon/Citadel/tree/main/skills/wiki Command: npx skills add https://github.com/SethGammon/Citadel --skill wiki-sethgammon
Markdown-first knowledge base where the LLM acts as librarian. Ingests raw sources, compiles and interlinks topic files, self-maintains an index. No vector DB or embeddings required -- uses LLM-native navigation over structured markdown up to ~400K words.
Initialize a wiki directory at the project root and begin ingesting sources with the /wiki workflow to build the knowledge base.
High-intent search queries and answers about installing and using this skill.
You can build a markdown-native knowledge base without vector embeddings by having the LLM ingest raw sources, compile interlinked topic files, and self-maintain a navigable index for reasoning over organized information.
Manage project documentation by initializing a wiki directory where the LLM compiles interlinked markdown topics and maintains an index, enabling direct navigation and question answering across your knowledge base.
Yes, you can answer questions over your project wiki without a vector database because the LLM reasons directly over structured markdown files and a self-maintained index up to approximately 400,000 words.
The best way to maintain a searchable wiki is using lifecycle commands to ingest raw sources, compact existing topics, and rebuild the index, ensuring the LLM can navigate interlinked knowledge without embeddings.
A key limitation is capacity, as this markdown-based knowledge management approach supports structured knowledge up to roughly 400,000 words, relying on LLM-native navigation rather than scalable vector search.
Simon-Copilot-StudioIngest sources into an interlinked markdown knowledge base with cross-links.
stefanbosakIndex and retrieve documentation from official sources, GitHub, and private repositories.
lvndryGenerate topic-specific digests with headlines, summaries, sources, and links.
rukikotooQuery the econometrics RAG knowledge base to retrieve relevant document chunks.
