Arscontexta

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

1. Add the marketplace to Claude Code:

   /plugin marketplace add agenticnotetaking/arscontexta

1. Install the plugin:

   /plugin install arscontexta@agenticnotetaking

1. Restart Claude Code, then run:

   /arscontexta:setup

1. Answer 2-4 questions about your domain (~20 minutes -- token-intensive but one-time)

1. The engine generates your complete knowledge system

1. Restart Claude Code again to activate generated hooks and skills

1. Run /arscontexta:help to 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 _schema blocks 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:

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:

Names adapt to your domain (notes/ might become reflections/, claims/, or decisions/), but the separation is invariant.

Commands

Plugin-Level (always available)

Generated (available after setup)

Processing Pipeline

The vault implements the 6 Rs, extending Cornell Note-Taking's 5 Rs with a meta-cognitive layer:

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:

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)