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Skills/DevOps & CI/CD
alirezarezvani avatar

Llm Wiki

alirezarezvani/claude-skills

This is a straightforward Wikipedia integration that lets Claude pull article content and summaries on demand. You'd reach for it when you need factual lookups during a conversation, whether that's checking historical dates, technical definitions, or general knowledge without leaving your workflow. The main value is having Wikipedia as a reliable fallback source instead of relying purely on Claude's training data. It's not reinventing anything, just making a common research pattern more convenient. Useful for fact-checking, filling knowledge gaps, or quickly grabbing context about topics that might have changed since Claude's knowledge cutoff.

installs
699
GitHub stars
28.8K
last updated
Aug 21, 2026
View on GitHubSave

Install

$ npx -y skills add alirezarezvani/claude-skills --skill llm-wiki --agent claude-code

Installs into .claude/skills of the current project.

Files

LLM 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

  1. 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.
  2. Query — LLM reads index.md first, drills into relevant pages, synthesizes with citations. Good answers get filed back into the wiki so explorations compound. See references/query-workflow.md.
  3. 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)

CommandPurpose
/wiki-initBootstrap 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-lintRun health check — contradictions, orphans, stale claims, gaps
/wiki-logShow recent log entries (uses unix tools on log.md)

Sub-agents (this plugin ships)

AgentWhen dispatched
wiki-ingestorDelegated ingest flow — reads source, proposes updates, applies after your approval
wiki-linterRuns the health-check workflow independently, reports findings
wiki-librarianAnswers 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.

ScriptPurpose
init_vault.pyCreate folder structure + seed CLAUDE.md, AGENTS.md, index.md, log.md
ingest_source.pyHelper: extract text/frontmatter from a source file, ready for LLM review
update_index.pyRegenerate index.md from wiki page frontmatter (category, date, source count)
append_log.pyAppend a standardized log entry ## [YYYY-MM-DD] <op> | <title>
wiki_search.pyBM25 search over wiki pages (standalone fallback when index.md isn't enough)
lint_wiki.pyFind orphans (no inbound links), stale pages, missing cross-refs, broken links
graph_analyzer.pyCompute link graph stats — hubs, orphans, clusters, disconnected components
export_marp.pyRender 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" to Ctrl+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 RAGLLM Wiki
Rediscover knowledge each queryKnowledge accumulates
Cross-references re-computed every timeCross-references pre-written and maintained
Contradictions surface only if you askContradictions flagged during ingest
Exploration disappears into chat historyGood answers re-filed as new pages
Scales by embeddings infrastructureScales 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 wiki
  • obsidian-vault (mattpocock) — lightweight Obsidian note helper; this skill is the maintained-wiki layer on top
  • rag-design — when wiki outgrows ~500 pages, use rag-design to bolt on a retrieval layer
  • mcp-design — expose the wiki as an MCP tool
  • agent-communication — for multi-agent wiki maintenance (ingestor + linter + librarian)

Reference docs

  • references/wiki-schema.md — full vault layout, page frontmatter, naming conventions
  • references/page-formats.md — entity, concept, source, comparison, synthesis templates
  • references/ingest-workflow.md — the detailed ingest flow the wiki-ingestor agent follows
  • references/query-workflow.md — query patterns, citation format, re-filing answers
  • references/lint-workflow.md — health-check heuristics
  • references/obsidian-setup.md — Obsidian plugins, hotkeys, vault config
  • references/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 tool
  • index.md.template, log.md.template — starter index and log
  • page-templates/ — entity, concept, source-summary, comparison, synthesis
  • example-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.

SKILL.md on GitHub

Sponsors

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Details

Repository
github.com/alirezarezvani/claude-skills
Categories
DevOps & CI/CD, Documentation, AI & Agent Building, Data Science & ML, Office & Documents
First seen
Jun 3, 2026

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