arscontexta
Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.
Ars Contexta
A second brain for your agent.
A Claude Code plugin that generates complete knowledge systems from conversation.
You describe how you think and work. The engine derives a cognitive architecture
-- folder structure, context files, processing pipeline, hooks, navigation maps,
and note templates -- tailored to your domain and backed by 249 research claims.
No templates. No configuration. Just conversation.
v0.8.0 · Claude Code plugin · MIT
Installation
Add the marketplace to Claude Code:
/plugin marketplace add agenticnotetaking/arscontextaInstall the plugin:
/plugin install arscontexta@agenticnotetakingRestart Claude Code, then run:
/arscontexta:setupAnswer 2-4 questions about your domain (~20 minutes -- token-intensive but one-time)
The engine generates your complete knowledge system
Restart Claude Code again to activate generated hooks and skills
Run
/arscontexta:helpto see everything available
What It Does
Most AI tools start every session blank. Ars Contexta changes that by generating
a persistent thinking system derived from how you actually work.
What you get:
- A vault -- plain markdown files connected by wiki links, forming a traversable
knowledge graph. No database, no cloud, no lock-in. - A processing pipeline -- skills that extract insights, find connections, update
old notes with new context, and verify quality. - Automation -- hooks that enforce structure on every write, detect maintenance
needs, capture session state, and auto-commit. - Navigation -- Maps of Content (MOCs) at hub, domain, and topic levels.
- Templates -- note templates with
_schemablocks as single source of truth. - A user manual -- 7 pages of domain-native documentation generated alongside.
The key differentiator: derivation, not templating. Every choice traces to
specific research claims. The engine reasons from principles about what your
domain needs and why.
The Setup Flow
/arscontexta:setup runs a 6-phase process:
| Phase | What Happens |
|---|---|
| Detection | Detects Claude Code environment and capabilities |
| Understanding | 2-4 conversation turns where you describe your domain |
| Derivation | Maps signals to eight configuration dimensions with confidence scoring |
| Proposal | Shows what will be generated and why, in your vocabulary |
| Generation | Produces all files: context file, folders, templates, skills, hooks, manual |
| Validation | Checks all 15 kernel primitives, runs pipeline smoke test |
The whole process takes about 20 minutes. It's token-intensive because the engine
reads research claims, reasons about your domain, and generates substantial output.
This is a one-time investment -- after setup, your agent remembers.
For advanced users: /arscontexta:setup --advanced to configure dimensions directly.
Three-Space Architecture
Every generated system separates content into three spaces:
| Space | Purpose | Growth |
|---|---|---|
| self/ | Agent persistent mind -- identity, methodology, goals | Slow (tens of files) |
| notes/ | Knowledge graph -- the reason the system exists | Steady (10-50/week) |
| ops/ | Operational coordination -- queue state, sessions | Fluctuating |
Names adapt to your domain (notes/ might become reflections/, claims/,
or decisions/), but the separation is invariant.
Commands
Plugin-Level (always available)
| Command | What It Does |
|---|---|
/arscontexta:setup |
Conversational onboarding -- generates your full system |
/arscontexta:help |
Contextual guidance and command discovery |
/arscontexta:tutorial |
Interactive walkthrough (learn by doing) |
/arscontexta:ask |
Query the research graph for methodology answers |
/arscontexta:health |
Run diagnostic checks on your vault |
/arscontexta:recommend |
Get architecture advice for your use case |
/arscontexta:architect |
Research-backed evolution guidance |
/arscontexta:add-domain |
Add a new knowledge domain to an existing system |
/arscontexta:reseed |
Re-derive from first principles when drift accumulates |
/arscontexta:upgrade |
Apply plugin knowledge base updates to your system |
Generated (available after setup)
| Command | What It Does |
|---|---|
/reduce |
Extract insights from sources |
/reflect |
Find connections, update MOCs |
/reweave |
Update older notes with new connections |
/verify |
Combined quality check: description + schema + health |
/validate |
Schema compliance checking |
/seed |
Create extraction task with duplicate detection |
/ralph |
Queue-based orchestration with fresh context per phase |
/pipeline |
End-to-end source processing |
/tasks |
Queue management |
/stats |
Vault metrics |
/graph |
Graph analysis |
/next |
Next-action recommendation |
/learn |
Research and grow |
/remember |
Mine session learnings |
/rethink |
Challenge system assumptions |
/refactor |
Structural improvements |
Processing Pipeline
The vault implements the 6 Rs, extending Cornell Note-Taking's 5 Rs with a
meta-cognitive layer:
| Phase | What Happens | Command |
|---|---|---|
| Record | Zero-friction capture into inbox/ | Manual |
| Reduce | Extract insights with domain-native categories | /reduce |
| Reflect | Find connections, update MOCs | /reflect |
| Reweave | Update older notes with new context | /reweave |
| Verify | Description + schema + health checks | /verify |
| Rethink | Challenge system assumptions | /rethink |
Fresh Context Per Phase
Each phase runs in its own context window via subagent spawning. LLM attention
degrades as context fills. By spawning a fresh subagent per phase, every phase
operates in the "smart zone."
/ralph 5
|-- Read queue, find next unblocked task
|-- Spawn subagent (fresh context)
| +-- Runs skill, updates task file, returns handoff
|-- Parse handoff, capture learnings
|-- Advance phase in queue
+-- Repeat for 5 tasks
Hooks
Four hooks automate quality enforcement:
| Hook | Event | What It Does |
|---|---|---|
| Session Orient | SessionStart |
Injects workspace tree, loads identity, surfaces maintenance signals |
| Write Validate | PostToolUse (Write) |
Schema enforcement on every note write |
| Auto Commit | PostToolUse (Write, async) |
Git auto-commit, non-blocking |
| Session Capture | Stop |
Persists session state to ops/sessions/ |
The Research Graph
The methodology/ directory contains 249 interconnected research claims
about tools for thought, knowledge management, and agent-native cognitive
architecture. These claims back every configuration decision.
Synthesizes
Zettelkasten -- Cornell Note-Taking -- Evergreen Notes -- PARA -- GTD -- Memory
Palaces -- Cognitive Science (extended mind, spreading activation, generation
effect) -- Network Theory (small-world topology, betweenness centrality) --
Agent Architecture (context windows, session boundaries, multi-agent patterns)
How Claims Back Decisions
Every kernel primitive includes cognitive_grounding linking to specific research:
- MOC hierarchy -- context-switching cost research (Leroy 2009)
- Description field -- progressive disclosure principles
- Wiki links -- spreading activation theory
Query directly: /arscontexta:ask "Why does my system use atomic notes?"
Semantic Search (optional)
qmd adds concept matching across vocabularies.
Not required -- the system works fully with ripgrep + MOC traversal.
/setup should perform this configuration automatically when semantic search is active.
The commands below are manual fallback/setup verification.
# Install qmd
npm install -g @tobilu/qmd
# or
bun install -g @tobilu/qmd
cd your-vault/
qmd init
qmd collection add . --name <notes_directory_name> --mask "<notes_directory_name>/**/*.md"
qmd embed
Create or merge .mcp.json in the vault root:
{
"mcpServers": {
"qmd": {
"command": "qmd",
"args": ["mcp"],
"autoapprove": [
"mcp__qmd__search",
"mcp__qmd__vector_search",
"mcp__qmd__deep_search",
"mcp__qmd__get",
"mcp__qmd__multi_get",
"mcp__qmd__status"
]
}
}
}
Keep qmd MCP configuration and tool preapproval in .mcp.json.
Prerequisites
| Dependency | Required | Purpose |
|---|---|---|
| Claude Code v1.0.33+ | Yes | Plugin host |
tree |
Yes | Workspace structure injection |
ripgrep (rg) |
Yes | YAML queries, schema validation |
| qmd | Optional | Semantic search |
Project Structure
arscontexta/
|-- .claude-plugin/
| |-- plugin.json # Plugin manifest
| +-- marketplace.json # Marketplace listing
|-- skills/ # 10 plugin-level commands
| |-- setup/ # Conversational onboarding
| |-- help/ # Contextual guidance
| |-- tutorial/ # Interactive walkthrough
| |-- ask/ # Query the research graph
| |-- health/ # Diagnostic checks
| |-- recommend/ # Architecture advice
| |-- architect/ # Evolution guidance
| |-- reseed/ # Re-derive from first principles
| |-- upgrade/ # Apply knowledge base updates
| +-- add-domain/ # Multi-domain extension
|-- skill-sources/ # 16 generated command templates
| |-- reduce/ # Extract insights
| |-- reflect/ # Find connections
| |-- reweave/ # Backward pass
| |-- verify/ # Combined quality check
| +-- ... # 12 more processing commands
|-- agents/
| +-- knowledge-guide.md # Pipeline subagent
|-- hooks/
| |-- hooks.json # Hook configuration
| +-- scripts/ # Hook implementations
|-- generators/
| |-- claude-md.md # CLAUDE.md template
| +-- features/ # 17 composable feature blocks
|-- methodology/ # 249 research claims
|-- reference/ # Core reference documents
| |-- kernel.yaml # 15 kernel primitives
| |-- three-spaces.md # Architecture spec
| +-- use-case-presets.md # Pre-validated configs
|-- platforms/ # Platform-specific adapters
| |-- claude-code/
| +-- shared/
|-- presets/ # Pre-validated configurations
|-- scripts/ # Utility scripts
+-- README.md
Development
Clone this repo and add the marketplace to Claude Code:
/plugin marketplace add ~/path-to-arscontexta
Install the plugin:
/plugin install arscontexta@agenticnotetaking
Every time you make changes, re-install the plugin:
/plugin uninstall arscontexta@agenticnotetaking
/plugin install arscontexta@agenticnotetaking
Key Files for Contributors
reference/kernel.yaml-- 15 primitives every system must includegenerators/features/*.md-- composable feature blocksskill-sources/*/SKILL.md-- generated command templatesskills/setup/SKILL.md-- the derivation enginereference/use-case-presets.md-- preset definitions
Presets
Three pre-validated configurations for common use cases:
| Preset | For | What You Get |
|---|---|---|
| Research | Academic work, literature reviews, synthesis | Atomic claims, citation tracking, methodology MOCs |
| Personal | Life management, journaling, relationships | Reflective notes, goal tracking, relationship MOCs |
| Experimental | Testing, iteration, rapid prototyping | Lightweight structure, fast capture, minimal ceremony |
Presets provide starting defaults. The derivation engine adapts from there based
on your conversation.
Roadmap
| Feature | Status |
|---|---|
| Claude Code plugin | Available |
| Marketplace listing | Available |
| Multi-agent processing | In progress |
Philosophy
The name connects to a tradition. Ars Combinatoria, Ars Memoria,
Ars Contexta: the art of context.
Llull's rotating wheels generated truth through combination. Bruno's memory wheels
created millions of image combinations. They were external thinking systems -- tools
to think with rather than just store in. The missing piece: they required a human
mind to do the traversing. Now LLMs can traverse. The wheels can spin again.
Built on Tools for Thought for Agents research.
License
MIT
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