LLM Wiki Knowledge System
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About this skill
Problem
Personal knowledge often lives in scattered articles, notes, PDFs, and clippings. An LLM can read a single document, but it usually lacks a durable maintenance loop, so ideas duplicate, conflict, or lose provenance over time. This skill turns raw material into a navigable Obsidian knowledge base.
How it works
- Init: after you provide the vault path, it creates
SCHEMA.md,raw/,wiki/,index.md, andlog.md. - Ingest: reads an article, file, or directory, extracts viewpoints, entities, concepts, cases, and actions, then writes summary pages and updates entity/concept pages.
- Links: uses
[[wikilinks]]so related pages can be followed during later queries. - Query: locates relevant pages from the index, reads multi-level context, and answers with citations; useful answers can become analysis pages.
- Lint: checks conflicts, orphan pages, missing pages, stale content, weak cross-references, and index consistency.
Boundaries
It depends on an Obsidian vault path and requires explicit first-time setup. raw/ is treated as read-only, so source material is not modified. It fits personal or team note organization, knowledge synthesis, and Q&A, but it is not a search engine, database, or automatic content production system.
Use Cases
- Digest collected articles and notes into an Obsidian Wiki, then maintain entity, concept, and index pages.
- Ask questions against the vault, following `[[wikilinks]]` to read context and return cited answers.
- Run periodic health checks to find conflicts, orphan pages, missing pages, stale content, and index drift.
- Ingest a long article or a folder of `.md` files, create source summaries, and connect related concepts.
Best For
- Engineers maintaining an Obsidian vault who want scattered notes turned into a queryable wiki.
- Developers doing technical research who need papers, articles, and product notes distilled into entity and concept pages.
- Knowledge managers maintaining shared notes who want conflict, broken-link, and index consistency checks.
- Researchers using LLM workflows who want cited answers from existing material and optional analysis pages.
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