What problem does it solve? Traditional RAG rediscovers knowledge from scratch on every query, losing cross-references and synthesis between sessions. This Skill maintains a persistent, compounding markdown wiki where sources are ingested once, cross-linked, and kept current over time. ## Core Features & Use Cases - Source Ingestion: Captures URLs, PDFs, and pasted text into an immutable raw/ layer with sha256 drift detection, then creates or updates cross-referenced wiki pages. - Query & Synthesis: Answers domain questions from compiled wiki pages and files valuable answers back as query or comparison pages. - Lint & Health Checks: Audits the wiki for orphan pages, broken wikilinks, stale content, contradictions, tag sprawl, and source drift. - Use Case: A researcher tracking AI/ML papers ingests each new arxiv paper into the wiki; the agent updates entity and concept pages, links them with [[wikilinks]], and later answers questions by synthesizing across all ingested sources. ## Quick Start Create a new wiki at ~/wiki for AI research and ingest this article URL into it.