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, so accumulated knowledge is immediately queryable. ## Core Features & Use Cases - Source Ingestion: Capture URLs, PDFs, and pasted text into an immutable raw/ layer with sha256 drift detection, then synthesize entity, concept, and comparison pages with wikilinks and provenance markers. - Query & Synthesis: Answer domain questions by reading the index and relevant pages, citing wiki sources, and filing valuable answers back as query or comparison pages. - Wiki Linting: Audit for orphan pages, broken wikilinks, stale content, contradictions, tag taxonomy violations, and source drift, with severity-grouped reports. - Use Case: A researcher tracking AI/ML developments ingests arxiv papers and articles weekly; the agent updates entity pages for models and labs, flags contradictions between sources, and keeps the Obsidian-compatible vault synchronized across devices. ## Quick Start Ask the agent to create a new wiki for your research domain and ingest your first source URL into it.
