obsidian-llm-wiki-local generates interlinked Obsidian markdown wikis using local LLMs. Its standout feature is a rejection feedback loop that refines article quality via user input.
obsidian-second-brain rewrites Obsidian vault pages autonomously using Claude Code agents, detecting contradictions and running scheduled maintenance for a self-healing AI knowledge base.
llm-wiki is a shell-based orchestration layer that turns LLM agents into a persistent, multi-agent research wiki. Supports up to 10 agents, deep investigations, and durable provenance tracking.
Explore how the email-marketing-bible Claude Code skill injects 68,000 words of sourced email marketing expertise into Claude AI, enabling expert audits, copywriting, and automation advice.
llm-wikid uses a CLAUDE.md schema to control a multi-phase ingest pipeline compiling markdown wiki pages for Obsidian, offering better Q&A at scale than RAG. Supports multiple AI agents and quality checks.
OpenKB compiles documents into a persistent, interlinked wiki using LLMs and PageIndex’s vectorless retrieval, supporting multi-LLM backends and interactive chat with persisted sessions.
understanding-math is a curated repository aggregating resources on mathematical literacy, notation, and proof techniques, bridging math concepts with programming needs in ML and cryptography.
Stash captures coding agent session transcripts for teams and builds a shared knowledge base without server-side LLM calls, preserving privacy and cutting costs.
llm_wiki uses a two-step chain-of-thought pipeline to build a self-maintaining knowledge base. It combines Tauri, knowledge graphs, and Louvain clustering for a unique personal wiki experience.
