Ross ROSS = Recommend OSS · open-source software intelligence for agents

nvk/llm-wiki

LLM-compiled knowledge bases for any AI agent. Parallel multi-agent research, thesis-driven investigation, source ingestion, wiki compilation, querying, and artifact generation. observed · 2026-08-28

github.com/nvk/llm-wiki · homepage · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

77/100

  • Activity 99
  • Release rhythm 87
  • Longevity 10

Flags: young

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 0.0
  • age_days: 151
  • days_rel: 10
  • days_push: 9
  • n_releases_24m: 65

Full methodology

Adoption not part of the score

1070 stars · 104 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A plugin that lets AI agents (Claude Code, OpenAI Codex, OpenCode, portable agents) compile and maintain LLM-curated knowledge bases as plain Markdown wikis. It orchestrates parallel multi-agent research, source ingestion, wiki compilation, read-only querying, session memory, and artifact generation, and is Obsidian-compatible.

Use cases

  • build a wiki knowledge base with AI agents
  • run parallel multi-agent research on a topic
  • ingest sources and compile them into cross-referenced articles
  • generate reports, slide decks, and study guides from research
  • query a knowledge base token-efficiently
  • keep session memory across agent runs
  • export project knowledge checkpoints for handoffs

When to choose

  • you use Claude Code, Codex, or OpenCode and want a persistent, agent-compiled knowledge base
  • you want Obsidian-compatible Markdown files you fully own
  • you need multi-agent research with provenance-rich source catalogs
  • you want to turn rough ideas into researched, approved project briefs

When to avoid

  • you need a hosted wiki or web UI rather than local Markdown files
  • you want a traditional RAG pipeline with vector embeddings instead of agent-compiled articles
  • your agent runtime is not Claude Code, Codex, OpenCode, or AGENTS.md-compatible

Facets

plugin · maturity active

agent-framework rag documentation search-engine workflow-automation llm-inference artificial-intelligence large-language-models developer-tools documentation cli cross-platform python claude-code agentic-workflow knowledge-base obsidian multi-agent-research markdown wiki codex opencode ai-agents retrieval-augmented-generation knowledge-management

2 sources

Member repositories

RepositoryRoleHealth v2
nvk/llm-wikimain77

For agents

markdown · JSON · MCP: product_card(name="nvk/llm-wiki")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem