What problem does it solve? Scattered research notes and saved articles decay into an unusable pile over time. This Skill turns an LLM into the maintainer of a persistent personal knowledge base: sources are stored immutably in a raw/ directory and compiled into structured, cross-linked wiki articles that compound in value with every ingest. ## Core Features & Use Cases - Ingest Pipeline: Fetch a source into raw/ with metadata headers, then compile it into wiki/ articles—merging into existing articles, creating new concept pages, and cascading updates to affected articles. - Query & Archive: Search the wiki via its index, synthesize cited answers, and optionally archive answers as point-in-time snapshot pages. - Lint & Quality Control: Auto-fix index inconsistencies, broken internal links, and raw references; report heuristic issues like contradictions, orphan pages, and outdated claims. - Use Case: You save a competitor analysis article. The Skill stores it in raw/ai-coding-tools/, merges its findings into an existing landscape article, updates the index and log, and flags a factual conflict with an older source. ## Quick Start Add this article to my wiki and tell me what I already know about its topic.
