This repository implements a personal knowledge management system centered around LLM-powered content processing. It follows a four-layer architecture: raw/ for immutable source materials, wiki/ for LLM-generated structured knowledge (summaries, concepts, indexes), brainstorming/ for intermediate outputs like chat logs and health reports, and artifacts/ for user-created work. The system processes various input formats (articles, books, PDFs, Facebook exports) through user-triggered commands like /compile and /convert-to-md, which leverage external tools (pandoc, pymupdf) and LLMs to extract insights and build interconnected knowledge networks. The core innovation lies in separating raw consumption from synthesized understanding, allowing users to accumulate source material without immediate processing, then periodically run LLM-driven synthesis to surface patterns across documents. Key workflows include extracting concepts that appear in multiple sources, maintaining bidirectional links between related ideas, and preserving tension between personal experience and external research in concept notes. The system emphasizes provenance tracking, with every synthesized piece linking back to its source via wikilinks. While the system relies on external LLMs and tools for its core functionality, it provides well-defined, reusable components for common data preparation tasks. The Facebook JSON-to-Markdown converter stands out as a robust, standalone script handling encoding normalization, media extraction, and frontmatter generation. The overall design demonstrates thoughtful consideration of knowledge work friction points, though reproducibility is hampered by undocumented environment dependencies and lack of sample data.