By skinnnyjay
LLM Wiki vault pattern: raw + wiki + outputs, Python CLI, ingest adapters, static viewer, D3 graphs, optional vault Git, research loop, ingestion security.
Run retrieval benchmarks (LME / LoCoMo / ConvoMem) from the vault; optional LLM rerank via API or local CLI.
Build static graph viewer + wiki-data.json into llm-wiki/wiki/.og/
Change vault settings after setup — MCP wiki_configure, CLI configure -i, or wiki-setup sections.
Show vault git diff (working tree or staged).
Audit vault git history by lifecycle phase (ingest, wiki, build, …) for flow progression.
Long-running research passes over many URLs or HN items; writes raw artifacts then hands off to wiki-ingest patterns.
Large multi-file edits across llm-wiki/wiki — index, cross-links, batch updates. Prefer llm-wiki git CLI when git.enabled.
Cleans and validates noisy raw/ markdown (HTML/PDF/OCR) into maintainable Markdown before wiki-ingest.
Extract Crunchbase company profiles, funding rounds, and investor data into raw/. Use for startup, investor, or market research.
Extract text from EPUB, MOBI, PDF, and AZW3 ebook files into raw/. Use when user has a local ebook or PDF to add to the vault.
Extract product listings, pricing, and auction data from Amazon, eBay, Etsy, Shopify into raw/. Use for product research or price tracking.
Extract GitHub repo README, issues, PRs, releases, and changelogs into raw/. Use when a GitHub URL is shared or tracking a project.
Extract LinkedIn profiles, jobs, and posts into raw/. Uses Firecrawl, archive.ph, Google cache, or manual export bypass hierarchy.
Admin access level
Server config contains admin-level keywords
Uses power tools
Uses Bash, Write, or Edit tools
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
This plugin requires configuration values that are prompted when the plugin is enabled. Sensitive values are stored in your system keychain.
firecrawl_api_keyFirecrawl API key for web extraction (optional)
${user_config.firecrawl_api_key}perplexity_api_keyPerplexity API key for news/current events research (optional)
${user_config.perplexity_api_key}brave_search_api_keyBrave Search API key (optional)
${user_config.brave_search_api_key}
llm-wiki is a Claude Code plugin (and a small Python CLI) that helps you keep a personal knowledge vault next to your projects. You capture sources into raw/, curate linked markdown in wiki/, and optionally generate a static viewer, wire MCP search, or turn on session memory—so your agent has a durable place to read and write, not a one-off chat dump.
It turns scattered source material into a maintained wiki your agent can keep improving over time—slash-command first (e.g. /llm-wiki:setup, /llm-wiki:ingest, /llm-wiki:build-og), without living in flag hell. Quick setup (docs site): skinnnyjay.github.io/wiki-llm/index.html#setup.
This repository is the plugin: commands, skills, templates, and bin/llm-wiki. After setup, your vault usually lives at ./llm-wiki/ inside whatever repo you chose (terminology is at the top of docs/QUICKSTART.md).
If I have seen further it is by standing on the shoulders of Giants.
— Isaac Newton, letter to Robert Hooke (1675).
The workflow borrows from Andrej Karpathy’s “LLM Wiki” gist and Karpathy on X—a simple pattern for turning sources into maintained notes—and from ideas in the MemPalace line of work (Milla & Ben on X; more context). The goal here is a concrete plugin for Claude Code (and friends) with ingest, validation, and agent-facing skills—not a generic “memory product.”
Feature list (vault, session memory, MCP recall, benchmarks, and more): docs/INSPIRATION.md. Alternate install paths and scripted examples: docs/INSTALL.md.
We treat the vault as sources first, then curated notes—not one undifferentiated pile of markdown.
raw/ — Ingested captures (files, URLs, feeds, APIs) land here with explicit paths; optional raw prepare cleans messy HTML/PDF/OCR before you merge.wiki/ — The maintained layer: wikilinks, wiki/index.md, wiki/log.md, and topic pages. wiki-ingest and wiki-maintainer help fold raw/ into structure without losing coherence.build-site for a static viewer (serve over HTTP, not file://)./llm-wiki:research, wiki-research-loop) plan sources → raw/ → wiki/ with logging.Evidence, trust, and why raw/ and wiki/ differ: ETHOS.md.
raw/ and later into model context. That includes prompt-injection patterns and bad-faith pages meant to mislead automations or readers—use at your discretion. This plugin does not sanitize the web for you. See skills/references/access-sources-disclaimer.md and ETHOS.md — Ingestion and security.We split vault knowledge, chat continuity, and retrieval evaluation—so “memory” stays understandable and under your control.
npx claudepluginhub skinnnyjay/wiki-llm --plugin llm-wikiHarness-native ECC operator layer - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Build and maintain an LLM-curated personal knowledge base in your project — Andrej Karpathy's LLM Wiki pattern, designed to scale to thousands of pages without becoming a context bottleneck. Now with an optional compiled graph layer for typed, provenance-backed relationships.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Complete collection of battle-tested Claude Code configs from an Anthropic hackathon winner - agents, skills, hooks, and rules evolved over 10+ months of intensive daily use
v9.44.1 — Patch release for Gemini environment/version detection and qwen auth gating. Run /octo:setup.
Comprehensive .NET development skills for modern C#, ASP.NET, MAUI, Blazor, Aspire, EF Core, Native AOT, testing, security, performance optimization, CI/CD, and cloud-native applications