Conversational derivation engine for agent-native knowledge systems
npx claudepluginhub agenticnotetaking/arscontextaGenerate research-backed knowledge systems from natural conversation. 15 kernel primitives, 26 commands, 249 research claims, 3 presets.
agenticnotetakingA 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 |
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