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.
# Add to your Claude Code skills
git clone https://github.com/agenticnotetaking/arscontextaGuides for using ide extensions skills like arscontexta.
Last scanned: 4/21/2026
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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
Add the marketplace to Claude Code:
/plugin marketplace add agenticnotetaking/arscontexta
Install the plugin:
/plugin install arscontexta@agenticnotetaking
Restart Claude Code, then run:
/arscontexta:setup
Answer 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:help to see everything available
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:
_schema blocks as single source of truth.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.
/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.
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.
| 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 |
| 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 |
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 |
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
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 methodology/ directory contains 249 interconnected research claims
about tools for thought, knowledge management, and agent-native cognitive
architecture. These claims back every configuration decision.
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)
Every kernel primitive includes cognitive_grounding linking to specific research:
Query directly: /arscontexta:ask "Why does my system use atomic notes?"
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.
| 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 |
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