arscontexta
v0.8.0Conversational derivation engine — generate agent-native memory architecture from natural conversation. 15 kernel primitives, 26 commands, 17 feature blocks, 3 presets.
by HeinrichMIT3.5kupdated 5 months ago
Source
git clone https://github.com/agenticnotetaking/arscontextaClone the source, then follow the repository's marketplace instructions for your runtime. The repository root is the plugin root.
Layout
├── .claude-plugin/plugin.json├── skills/add-domain/SKILL.md├── skills/architect/SKILL.md├── skills/ask/SKILL.md├── skills/health/SKILL.md├── skills/help/SKILL.md├── skills/recommend/SKILL.md├── skills/reseed/SKILL.md├── skills/setup/SKILL.md├── skills/tutorial/SKILL.md└── skills/upgrade/SKILL.md
Skills10
Add a new knowledge domain to your existing system. Derives domain-specific configuration through conversation, generates domain folders, templates, and vocabulary while preserving and connecting to your existing architecture.
Research-backed evolution advice for your knowledge system. Analyzes health reports, friction patterns, and derivation history to propose specific changes with research justification. Never auto-implements — proposals require your approval.
Query the bundled research knowledge graph for methodology guidance. Routes questions through a 3-tier knowledge base — WHY (research claims), HOW (guidance docs), WHAT IT LOOKS LIKE (domain examples) — plus structured reference documents. Returns research-backed answers grounded in specific claims with practical application to the user's system. Triggers on "/ask", "/ask [question]", "why does my system...", "how should I...".
Run condition-based vault health diagnostics. 8 categories — schema compliance, orphan detection, link health, description quality, three-space boundaries, processing throughput, stale notes, MOC coherence. 3 modes — quick (schema+orphans+links), full (all 8), three-space (boundary violations only). Returns actionable FAIL/WARN/PASS report with specific fixes ranked by impact. Triggers on "/health", "check vault health", "maintenance report", "what needs fixing".
Contextual guidance and command discovery. Three modes — narrative (first-time), contextual (mid-task), compact (quick reference). Shows available commands, active skills, and intelligent suggestions based on vault state. Triggers on "/help", "what can I do", "show commands", "how does this work".
Get research-backed architecture advice for your knowledge system. Describe your use case, constraints, and goals — get specific recommendations grounded in TFT research with rationale for each decision. Triggers on "/recommend", "what would you recommend", "architecture advice", "knowledge system for".
Re-derive your knowledge system from first principles when structural drift accumulates. Analyzes dimension incoherence, vocabulary mismatch, boundary dissolution, and template divergence. Preserves all content while restructuring architecture.
Scaffold a complete knowledge system. Detects platform, conducts conversation, derives configuration, generates everything. Validates against 15 kernel primitives. Triggers on "/setup", "/setup --advanced", "set up my knowledge system", "create my vault".
Interactive walkthrough for new users. Learn by doing — each step creates real content in your vault. Three tracks (researcher, manager, personal) with a universal learning arc. Triggers on "/tutorial", "walk me through", "how do I use this".
Apply plugin knowledge base updates to an existing generated system. Consults the Ars Contexta research graph for methodology improvements, proposes skill upgrades with research justification. Never auto-implements. Triggers on "/upgrade", "upgrade skills", "check for improvements", "update methodology".
Manifests1
{
"name": "arscontexta",
"version": "0.8.0",
"description": "Conversational derivation engine — generate agent-native memory architecture from natural conversation. 15 kernel primitives, 26 commands, 17 feature blocks, 3 presets.",
"author": {
"name": "Heinrich",
"url": "https://arscontexta.org"
},
"homepage": "https://arscontexta.org",
"repository": "https://github.com/agenticnotetaking/arscontexta",
"license": "MIT",
"keywords": [
"knowledge-management",
"tools-for-thought",
"memory-system",
"derivation",
"cognitive-architecture",
"agent-native",
"zettelkasten",
"knowledge-graph"
]
}