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Llm Wiki

Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki",…

aillmrag
By alirezarezvani
19k2.7kUpdated 3 days agoPythonMIT

Skill Content

# 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

```bash
# 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" 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 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 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.

How to use

  1. Copy the skill content above
  2. Create a .claude/skills directory in your project
  3. Save as .claude/skills/claude-skills-llm-wiki.md
  4. Use /claude-skills-llm-wiki in Claude Code to invoke this skill

Claude Code Skills & Plugins — Agent Skills for Every Coding Tool

345 production-ready Claude Code skills, plugins, and agent skills for 13 AI coding tools.

The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 9 more coding agents. Reusable expertise packages covering engineering, DevOps, marketing (incl. AEO — Answer Engine Optimization for LLM citation), security (PreToolUse hooks), compliance, C-level advisory (incl. founder-mode CFO/CMO/CRO/CPO/COO/CHRO/CISO/GC/CDO/CAIO/CCO/VPE personas + 21 /cs:* slash commands), productivity (capture/email/reflect), an academic research stack (litreview/grants/dossier/patent/syllabus/pulse/notebooklm + hybrid router), and enterprise Research Operations (clinical-research/research-finance/market-research/product-research, v2.9.0).

Works with: Claude Code · OpenAI Codex · Gemini CLI · OpenClaw · Hermes Agent1 · Mistral Vibe2 · Cursor · Aider · Windsurf · Kilo Code · OpenCode · Augment · Antigravity

License: MIT Skills Agents Personas Commands Stars SkillCheck Validated

5,200+ GitHub stars — the most comprehensive open-source Claude Code skills & agent plugins library.


What Are Claude Code Skills & Agent Plugins?

Claude Code skills (also called agent skills or coding agent plugins) are modular instruction packages that give AI coding agents domain expertise they don't have out of the box. Each skill includes:

  • SKILL.md — structured instructions, workflows, and decision frameworks
  • Python tools — 579 CLI scripts (all stdlib-only, zero pip installs)
  • Reference docs — 702 templates, checklists, and domain-specific knowledge files

One repo, thirteen platforms. Works natively as Claude Code plugins, Codex agent skills, Gemini CLI skills, Hermes Agent skills, Mistral Vibe skills, and converts to more tools via scripts/convert.sh. All 579 Python tools run anywhere Python runs.

Skills vs Agents vs Personas

SkillsAgentsPersonas
PurposeHow to execute a taskWhat task to doWho is thinking
ScopeSingle domainSingle domainCross-domain
VoiceNeutralProfessionalPersonality-driven
Example"Follow these steps for SEO""Run a security audit""Think like a startup CTO"

All three work together. See Orchestration for how to combine them.


Quick Install

Gemini CLI (New)

# Clone the repository
git clone https://github.com/alirezarezvani/claude-skills.git
cd claude-skills

# Run the setup script
./scripts/gemini-install.sh

# Start using skills
> activate_skill(name="senior-architect")

Claude Code (Recommended)

# Add the marketplace
/plugin marketplace add alirezarezvani/claude-skills

# Install by domain
/plugin install engineering-skills@claude-code-skills          # 24 core engineering
/plugin install engineering-advanced-skills@claude-code-skills  # 25 POWERFUL-tier
/plugin install product-skills@claude-code-skills               # 12 product skills
/plugin install marketing-skills@claude-code-skills             # 43 marketing skills
/plugin install ra-qm-skills@claude-code-skills                 # 12 regulatory/quality
/plugin install pm-skills@claude-code-skills                    # 6 project management
/plugin install c-level-skills@claude-code-skills               # 28 C-level advisory (full C-suite)
/plugin install business-growth-skills@claude-code-skills       # 4 business & growth
/plugin install finance-skills@claude-code-skills               # 2 finance (analyst + SaaS metrics)

# Or install individual skills
/plugin install skill-security-auditor@claude-code-skills       # Security scanner
/plugin install playwright-pro@claude-code-skills                  # Playwright testing toolkit
/plugin install self-improving-agent@claude-code-skills         # Auto-memory curation
/plugin install content-creator@claude-code-skills              # Single skill

OpenAI Codex

npx agent-skills-cli add alirezarezvani/claude-skills --agent codex
# Or: git clone + ./scripts/codex-install.sh

OpenClaw

bash <(curl -s https://raw.githubusercontent.com/alirezarezvani/claude-skills/main/scripts/openclaw-install.sh)

Manual Installation

git clone https://github.com/alirezarezvani/claude-skills.git
# Copy any skill folder to ~/.claude/skills/ (Claude Code) or ~/.codex/skills/ (Codex)

Multi-Tool Support (New)

Convert all 345 skills to 9 AI coding tools with a single script:

ToolFormatInstall
Cursor.mdc rules./scripts/install.sh --tool cursor --target .
AiderCONVENTIONS.md./scripts/install.sh --tool aider --target .
Kilo Code.kilocode/rules/./scripts/install.sh --tool kilocode --target .
Windsurf.windsurf/skills/./scripts/install.sh --tool windsurf --target .
OpenCode.opencode/skills/./scripts/install.sh --tool opencode --target .
Augment.augment/rules/./scripts/install.sh --tool augment --target .
Antigravity~/.gemini/antigravity/skills/./scripts/install.sh --tool antigravity
Hermes Agent~/.hermes/skills/python scripts/sync-hermes-skills.py --verbose
Mistral Vibe~/.vibe/skills/./scripts/vibe-install.sh

How it works:

# 1. Convert all skills to all tools (takes ~15 seconds)
./scripts/convert.sh --tool all

# 2. Install into your project (with confirmation)
./scripts/install.sh --tool cursor --target /path/to/project

# Or use --force to skip confirmation:
./scripts/install.sh --tool aider --target . --force

# 3. Verify
find .cursor/rules -name "*.mdc" | wc -l  # Should show 346

Each tool gets:

  • ✅ All 345 skills converted to native format
  • ✅ Per-tool README with install/verify/update steps
  • ✅ Support for scripts, references, templates where applicable
  • ✅ Zero manual conversion work

Run ./scripts/convert.sh --tool all to generate tool-specific outputs locally.


Skills Overview

345 skills across 17 domains:

DomainSkillsHighlightsDetails
🔧 Engineering — Core51Architecture, frontend, backend, fullstack, QA, DevOps, SecOps, AI/ML, data, Playwright Pro (test gen, flaky fix, migrations), self-improving agent (auto-memory curation), security suite, a11y auditengineering-team/
⚡ Engineering — POWERFUL78Agent designer, RAG architect, database designer, CI/CD builder, security auditor, MCP builder, AgentHub, Helm charts, Terraform, self-eval, llm-wiki, tc-tracker, autoresearch-agent, reliability portfolio (feature-flags-architect, kubernetes-operator, chaos-engineering, slo-architect), ship-gate, security-guidance PreToolUse hook, Matt Pocock skills (write-a-skill, caveman, grill-me, handoff, grill-with-docs)engineering/
🎯 Product17Product manager, agile PO, strategist, UX researcher, UI design, landing pages, SaaS scaffolder, analytics, experiment designer, discovery, roadmap communicator, code-to-prd, apple-hig-expertproduct-team/
📣 Marketing468 pods: Content, SEO + AEO (aeo — E-E-A-T audit, citation tracking across 5 LLMs), CRO, Channels, Growth, Intelligence, Sales + context foundation + orchestration routermarketing-skill/
🚀 Productivity6capture (brain-dump-to-action), email pair (inbox-setup + inbox-triage), reflect (journal), handoff (Matt Pocock-inspired), andreessen (market-first decision mode)productivity/
🎨 Marketing (top-level)1landing — single-file HTML landing-page generator (4 design styles, GSAP patterns, brand palette validator)marketing/
🔬 Research (academic)8research orchestrator (hybrid router + fallback) + 7 specialists: pulse, litreview, grants (NIH), dossier, patent, syllabus, notebooklmresearch/
🧪 Research Operations ✨v2.9.05Enterprise/cross-functional research: orchestrator + clinical-research (study design), research-finance (R&D program finance), market-research (sizing/survey/segmentation), product-research (user research) — each with onboarding + customization + opt-in autoresearch bridgeresearch-ops/
📋 Project Management9Senior PM, scrum master, Jira, Confluence, Atlassian admin, templates + bundled Atlassian Remote MCPproject-management/
🏥 Regulatory & QM18ISO 13485, MDR 2017/745, FDA, ISO 27001, GDPR, SOC 2, CAPA, risk managementra-qm-team/
🛡️ Compliance OS9Compliance operating system — controls, evidence, audit-readiness workflowscompliance-os/
💼 C-Level Advisory66Full C-suite (CEO/CTO/CFO/CMO/CRO/CPO/COO/CHRO/CISO/GC/CDO/CAIO/CCO/VPE) + founder-mode agents + orchestration + board meetings + culture & collaborationc-level-advisor/
📈 Business & Growth5Customer success, sales engineer, revenue ops, contracts & proposals, BizDev toolkitbusiness-growth/
🏭 Business Operations7Orchestrator + process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizerbusiness-operations/
🤝 Commercial8Orchestrator + pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecastercommercial/
💰 Finance4Financial analyst (DCF, budgeting, forecasting), SaaS metrics coach, business investment advisorfinance/

Personas

Pre-configured agent identities with curated skill loadouts, workflows, and distinct communication styles. Personas go beyond "use these skills" — they define how an agent thinks, prioritizes, and communicates.

PersonaDomainBest For
Startup CTOEngineering + StrategyArchitecture decisions, tech stack selection, team building, technical due diligence
Growth MarketerMarketing + GrowthContent-led growth, launch strategy, channel optimization, bootstrapped marketing
Solo FounderCross-domainOne-person sta

Footnotes

  1. Hermes Agent is BYO-sync tier: the repo ships a pre-generated .hermes/skills/claude-skills/ tree, but you run python scripts/sync-hermes-skills.py once locally to install into ~/.hermes/skills/. Uses the same agentskills.io SKILL.md standard — no format conversion.

  2. Mistral Vibe is also BYO-sync tier: the repo ships a pre-generated .vibe/skills/claude-skills/ tree, run ./scripts/vibe-install.sh once locally to install into ~/.vibe/skills/. Same agentskills.io SKILL.md standard — no format conversion. Docs: https://docs.mistral.ai/mistral-vibe/agents-skills.

View source on GitHub