ask

EXECUTE NOW

Question: $ARGUMENTS

If no question provided, ask the user what they want to know.

Execute these steps:

1. Classify the question — determine which knowledge base tier(s) to consult (see Query Classification below)
2. Search the knowledge base — route to appropriate tiers based on classification
3. Read relevant claims and docs — load 3-7 most relevant sources fully (use mcp__qmd__multi_get when reading multiple IDs)
4. Check user context — read ops/derivation.md if the question involves their specific system
5. Synthesize an answer — weave claims into a coherent, opinionated argument
6. Cite sources — reference specific claims and documents so the user can explore further

START NOW. Reference below explains routing and synthesis methodology.

The Three-Tier Knowledge Base

The plugin's knowledge base has three distinct parts, each serving a different function. Effective answers often draw from multiple tiers.

Tier 1: Research Graph (WHY)

Location: ${CLAUDE_PLUGIN_ROOT}/methodology/ — filter by kind: research Content: 213 interconnected research claims grounded in cognitive science, knowledge system theory, and agent cognition research. Use for: Questions about principles, trade-offs, why things work, theoretical foundations.

What it contains:

• Claims about how knowledge systems work (human and agent)
• Cognitive science foundations (working memory, attention, retrieval)
• Methodology comparisons (Zettelkasten vs PARA, atomic vs compound)
• Design dimensions (trade-off spectrums with poles and decision factors)
• Failure modes and anti-patterns
• Agent-specific constraints (context windows, session boundaries)

Search strategy: Use mcp__qmd__deep_search (highest quality, LLM-reranked) for conceptual questions. Use mcp__qmd__vector_search for semantic exploration. Use mcp__qmd__search for known terminology. All searches use the methodology collection.

Tier 2: Guidance Docs (HOW)

Location: ${CLAUDE_PLUGIN_ROOT}/methodology/ — filter by kind: guidance Content: 9 operational documents covering procedures, workflows, and implementation rationale. Use for: Questions about how to do things, operational best practices, workflow mechanics.

Documents include:

• Schema enforcement rationale and procedures
• Pipeline philosophy and processing workflow
• MOC methodology and navigation patterns
• Maintenance patterns and condition-based triggers
• Memory architecture and session management
• Vocabulary transformation procedures
• Failure mode prevention patterns
• Multi-domain composition rules
• Onboarding and evolution decisions

Search strategy: mcp__qmd__search with keywords from the question using the methodology collection. To narrow to guidance docs, add kind:guidance to your grep filter on results.

Tier 3: Domain Examples (WHAT IT LOOKS LIKE)

Location: ${CLAUDE_PLUGIN_ROOT}/methodology/ — filter by kind: example Content: 12 domain-specific compositions showing what generated vaults look like in practice. Use for: Questions about how to apply methodology to specific domains, inspiration for novel domain mapping.

Examples include domains like:

• Research vaults (academic literature reviews, claim extraction)
• Personal assistant vaults (life management, therapy, health wellness)
• Project management vaults (decision tracking, stakeholder context)
• Creative vaults (worldbuilding, character tracking)
• Engineering, legal, trading, student learning, relationships

Search strategy: Use mcp__qmd__vector_search across the methodology collection for semantic domain matching. To list all examples: rg '^kind: example' ${CLAUDE_PLUGIN_ROOT}/methodology/.

Reference Documents (structured derivation context)

Location: ${CLAUDE_PLUGIN_ROOT}/reference/ Content: Structured reference documents supporting derivation and system architecture. Use for: Deep dives into specific architectural topics, cross-referencing dimension positions, understanding interaction constraints.

Core Architecture:

• methodology.md — universal principles and processing pipeline
• components.md — component blueprints and feature blocks
• kernel.yaml — the 12 non-negotiable primitives
• three-spaces.md — self/notes/ops architecture and boundary rules

Configuration & Derivation:

• dimension-claim-map.md — which research claims inform which dimensions
• interaction-constraints.md — how dimension choices create pressure on others
• tradition-presets.md — named points in configuration space
• vocabulary-transforms.md — universal-to-domain term mapping
• derivation-validation.md — validation tests for derived systems

Behavioral & Quality:

• personality-layer.md — personality derivation and encoding
• conversation-patterns.md — worked examples of full derivation paths
• failure-modes.md — how knowledge systems die and prevention patterns

Lifecycle & Operations:

• use-case-presets.md — preset configurations for common domains
• session-lifecycle.md — session rhythm, context budget, orient-work-persist
• evolution-lifecycle.md — seed-evolve-reseed, condition-based maintenance
• self-space.md — agent identity generation, self/ architecture
• semantic-vs-keyword.md — search modality selection guidance
• open-questions.md — unresolved research questions and deferred items

Also read: claim-map.md — the routing index showing which claims map to which topics. Start here when you need to find relevant claims quickly.

Query Classification

Before searching, classify the user's question to determine which tier(s) to consult.

Classification Rules

Multi-Tier Questions

Many questions require consulting multiple tiers. The classification above shows primary and secondary tiers. Always check: would the answer be stronger with evidence from another tier?

Example multi-tier routing:

Question: "Why does my system use atomic notes instead of longer documents?"

1. WHY tier — search research graph for claims about atomicity, granularity, composability
2. Reference — check dimension-claim-map.md for the granularity dimension's informing claims
3. User context — check ops/derivation.md for their specific granularity position and reasoning
4. WHAT tier — optionally pull an example showing what atomic notes look like in a similar domain

Question: "How should I handle therapy session notes that are very long?"

1. HOW tier — search guidance for processing workflow, chunking strategies
2. WHAT tier — check examples for therapy or personal domains with similar challenges
3. WHY tier — search for claims about context degradation, chunking benefits, large