
LLM Wiki
FreeBuild and maintain a personal knowledge base in Obsidian.
Free · Opens the source repo
What LLM Wiki does
The LLM Wiki skill is designed for users who want to create and maintain a persistent personal knowledge base using Obsidian. This skill leverages the capabilities of Claude Code or other AI agents to incrementally ingest sources, update entity and concept pages, and maintain cross-references within a structured markdown vault. By adopting a compounding knowledge approach, the skill ensures that information is not just retrieved at query time but is integrated into a cohesive and evolving knowledge base. This allows users to curate their knowledge effectively, making it readily accessible and up-to-date.
The architecture of the LLM Wiki skill consists of three main layers. The first layer, raw/, serves as an immutable source of truth where users can store articles, papers, and other reference materials. The second layer, wiki/, is managed by the LLM, which creates and updates pages based on the ingested sources. The third layer contains schema files that define the conventions and workflows for knowledge management. This structure enables users to maintain a clear separation between raw data and processed knowledge, facilitating better organization and retrieval.
Core operations of the skill include ingesting sources, querying the knowledge base, and performing health checks on the wiki. Users can initiate the ingestion process to read a source, discuss its contents, and update relevant pages in the wiki. The querying feature allows users to ask questions and receive synthesized answers, which can then be filed back into the wiki for future reference. Additionally, the linting operation checks for inconsistencies, stale claims, and missing cross-references, ensuring the knowledge base remains accurate and comprehensive.
This skill is particularly useful for individuals engaged in research, personal development, or team collaboration. It serves as a powerful tool for anyone looking to build a structured and maintainable knowledge repository that evolves over time, making it ideal for long-term projects or ongoing learning.
When to use it
Use this skill when you want to create a structured personal knowledge base in Obsidian that grows and evolves as you add new sources.
When not to use it
Avoid this skill if you require one-time answers from fixed documents or do not plan to continuously add new sources to your knowledge base.
What you can build with it
Research Projects
Use the LLM Wiki to compile and synthesize information from multiple sources for a comprehensive research project.
Personal Development
Track your goals and insights over time by maintaining a personal journal and knowledge base within Obsidian.
Team Collaboration
Create an internal wiki for your team that is continuously updated with notes from meetings and discussions.
How to install LLM Wiki
View source1. Install with the skills CLI
npx skills add alirezarezvani/claude-skills/llm-wiki --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by alirezarezvaniLLM Wiki — Second Brain for Claude Code + Obsidian
Inspired by Andrej Karpathy's LLM Wiki pattern (gist). This skill turns Claude Code (or any agent CLI) into a disciplined wiki maintainer that incrementally builds and maintains a persistent, interlinked Obsidian vault as you feed it sources. The knowledge compounds — cross-references, contradictions, and synthesis are already there when you query.
Core principle
Most LLM+docs workflows are RAG: retrieve fragments at query time, synthesize from scratch, forget. The wiki is compounding: sources are read once, integrated into a persistent markdown knowledge base, and kept current. You curate and ask; the LLM reads, files, cross-references, and maintains.
Obsidian is the IDE. The LLM is the programmer. The wiki is the codebase.
When to use
- Personal: track goals, health, psychology, journaling, self-improvement
- Research: deep dives over weeks on a topic — papers, articles, reports, evolving thesis
- Book companion: file chapters as you read; build a fan-wiki-style companion for characters, themes, plot threads
- Business/team: internal wiki fed by Slack, meeting notes, calls — LLM does maintenance nobody else wants to do
- Competitive analysis, due diligence, trip planning, course notes, hobby deep-dives
Do NOT use when: you need one-shot Q&A over a fixed document (use RAG), you don't plan to add sources over time, or you don't want Obsidian in the loop.
Architecture (three layers)
vault/
├── raw/ # Layer 1 — IMMUTABLE source of truth
│ ├── <source files> # Articles, papers, PDFs, images, data
│ └── assets/ # Downloaded images from clipped articles
├── wiki/ # Layer 2 — LLM-owned knowledge base
│ ├── index.md # Content catalog (LLM updates every ingest)
│ ├── log.md # Append-only timeline (## [YYYY-MM-DD] <op> | <title>)
│ ├── entities/ # Person/Org/Place pages
│ ├── concepts/ # Ideas, theories, frameworks
│ ├── sources/ # One summary page per ingested source
│ ├── comparisons/ # Cross-source analysis pages
│ └── synthesis/ # High-level syntheses, theses, overviews
├── CLAUDE.md # Schema + conventions (Claude Code)
└── AGENTS.md # Same content, for Codex/Cursor/Antigravity
- Layer 1 (raw/) — you own. LLM only reads; never writes.
- Layer 2 (wiki/) — LLM owns. It creates, updates, and cross-references pages. You read it.
- Layer 3 (CLAUDE.md / AGENTS.md) — the schema. Conventions, workflows, frontmatter rules. Co-evolved by you and the LLM.
Three core operations
- Ingest — LLM reads a source, discusses takeaways with you, writes a source summary, updates 10-15 relevant pages, updates index, appends to log. See
references/ingest-workflow.md. - Query — LLM reads
index.mdfirst, drills into relevant pages, synthesizes with citations. Good answers get filed back into the wiki so explorations compound. Seereferences/query-workflow.md. - Lint — Health check: contradictions, stale claims, orphan pages, missing cross-refs, concepts mentioned but lacking their own page, data gaps to fill with web search. See
references/lint-workflow.md.
Quick start
# 1. Initialize a vault (in Obsidian's vault directory)
python scripts/init_vault.py --path ~/vaults/research --topic "LLM interpretability"
# 2. Drop a source into raw/, then ingest
/wiki-ingest ~/vaults/research/raw/anthropic-monosemanticity.pdf
# 3. Ask questions (answers can be re-filed into the wiki)
/wiki-query "how does monosemanticity compare to mechanistic interpretability?"
# 4. Periodic health check
/wiki-lint
# 5. See the timeline
/wiki-log --last 10
Slash commands (this plugin ships)
| Command | Purpose |
|---|---|
/wiki-init | Bootstrap a fresh vault with schema files + starter structure |
/wiki-ingest <path> | Read a source, discuss, update wiki, log it |
/wiki-query <question> | Search wiki, synthesize answer, offer to file back |
/wiki-lint | Run health check — contradictions, orphans, stale claims, gaps |
/wiki-log | Show recent log entries (uses unix tools on log.md) |
Sub-agents (this plugin ships)
| Agent | When dispatched |
|---|---|
wiki-ingestor | Delegated ingest flow — reads source, proposes updates, applies after your approval |
wiki-linter | Runs the health-check workflow independently, reports findings |
wiki-librarian | Answers queries using index-first search, synthesizes with citations |
Python tools (scripts/)
All tools are standard library only (no pip installs). Run with python scripts/<tool>.py --help.
| Script | Purpose |
|---|---|
init_vault.py | Create folder structure + seed CLAUDE.md, AGENTS.md, index.md, log.md |
ingest_source.py | Helper: extract text/frontmatter from a source file, ready for LLM review |
update_index.py | Regenerate index.md from wiki page frontmatter (category, date, source count) |
append_log.py | Append a standardized log entry ## [YYYY-MM-DD] <op> | <title> |
wiki_search.py | BM25 search over wiki pages (standalone fallback when index.md isn't enough) |
lint_wiki.py | Find orphans (no inbound links), stale pages, missing cross-refs, broken links |
graph_analyzer.py | Compute link graph stats — hubs, orphans, clusters, disconnected components |
export_marp.py | Render a wiki page (or subtree) to a Marp slide deck |
Cross-tool compatibility
The vault's schema lives in CLAUDE.md (Claude Code) or AGENTS.md (Codex/Cursor/Antigravity/OpenCode). The same content works in both. This plugin ships both templates. For per-tool setup instructions see references/cross-tool-setup.md.
CLAUDE.md → Claude Code
AGENTS.md → Codex CLI, Cursor, Antigravity, OpenCode, Gemini CLI
.cursorrules → legacy Cursor (pre-AGENTS.md)
The scripts are pure Python stdlib → run identically everywhere. Only the loader file changes per tool.
Obsidian setup (recommended)
- Obsidian Web Clipper — browser extension; converts web articles to markdown and drops them in
raw/ - Download images locally — Settings → Files and links → Attachment folder path =
raw/assets/. Settings → Hotkeys → bind "Download attachments for current file" toCtrl+Shift+D - Graph view — see hubs/orphans; essential for spotting structural problems
- Marp plugin — Markdown-based slide decks directly from wiki pages
- Dataview plugin — dynamic tables/lists over page frontmatter (tags, dates, source counts)
- Git — the vault is a plain markdown repo; version it
Full setup walkthrough: references/obsidian-setup.md
Why this works (vs plain RAG)
| Plain RAG | LLM Wiki |
|---|---|
| Rediscover knowledge each query | Knowledge accumulates |
| Cross-references re-computed every time | Cross-references pre-written and maintained |
| Contradictions surface only if you ask | Contradictions flagged during ingest |
| Exploration disappears into chat history | Good answers re-filed as new pages |
| Scales by embeddings infrastructure | Scales by markdown + index.md + optional local search |
At ~100 sources / hundreds of pages, index.md + filesystem search is enough. Past that, layer in a local search tool like qmd or use scripts/wiki_search.py.
Related skills (chains via context: fork)
This skill is marked context: fork so other skills can chain into it:
para-memory-files— PARA-method memory; complementary as long-term personal memory that feeds sources into the wikiobsidian-vault(mattpocock) — lightweight Obsidian note helper; this skill is the maintained-wiki layer on toprag-design— when wiki outgrows ~500 pages, use rag-design to bolt on a retrieval layermcp-design— expose the wiki as an MCP toolagent-communication— for multi-agent wiki maintenance (ingestor + linter + librarian)
Reference docs
references/wiki-schema.md— full vault layout, page frontmatter, naming conventionsreferences/page-formats.md— entity, concept, source, comparison, synthesis templatesreferences/ingest-workflow.md— the detailed ingest flow the wiki-ingestor agent followsreferences/query-workflow.md— query patterns, citation format, re-filing answersreferences/lint-workflow.md— health-check heuristicsreferences/obsidian-setup.md— Obsidian plugins, hotkeys, vault configreferences/cross-tool-setup.md— per-tool setup (Codex, Cursor, Antigravity, etc.)references/memex-principles.md— Bush's Memex, why the LLM changes the maintenance math
Templates (assets/)
CLAUDE.md.template,AGENTS.md.template,.cursorrules.template— schema loaders per toolindex.md.template,log.md.template— starter index and logpage-templates/— entity, concept, source-summary, comparison, synthesisexample-vault/— small worked example you can study or copy
Iron rule
The LLM never edits files in raw/. Ever. Sources are immutable. All LLM writes go to wiki/. If you need to correct a source, do it in raw/ yourself — then re-ingest.
Frequently asked questions about LLM Wiki
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