llm-wiki – skill Dữ liệu & Khoa học cho agent AI
Dùng khi xây dựng hoặc duy trì một cơ sở tri thức cá nhân bền vững (second brain) trong Obsidian, nơi LLM tiếp nhận nguồn từng bước, cập nhật các trang thực thể/khái niệm, duy trì tham chiếu chéo và giữ bản tổng hợp luôn cập nhật. Kích hoạt gồm "second brain", "Obsidian wiki", "quản lý tri thức cá nhân", "ingest
Cài skill llm-wiki bằng một lệnh
Chọn công cụ bạn đang dùng, copy lệnh và dán vào terminal. Skill sẽ nằm trong thư mục skills của công cụ đó và sẵn sàng dùng ở phiên làm việc tiếp theo.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/llm-wiki-7dd2d.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /llm-wiki – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/llm-wiki-7dd2d.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $llm-wiki – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/llm-wiki-7dd2d.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /llm-wiki – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/llm-wiki-7dd2d.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /llm-wiki – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
LLM Wiki — Second Brain for Claude Code + Obsidian
Inspired by Andrej Karpathy's LLM Wiki pattern ([gist](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f)). 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 10Slash 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](https://github.com/tobi/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 i
… (nội dung đầy đủ có trong gói tải về)
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