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/ask

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

From plugin
arscontexta
3.5k10 skills1 agent2 hooks
Install
$ npx -y skills add agenticnotetaking/arscontexta --skill ask --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ask

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

ask.SKILL.md
name: ask
description: 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...".
version: "1.0"
generated_from: "arscontexta-v1.6"
context: fork
model: opus
allowed-tools: Read, Grep, Glob, mcp__qmd__search, mcp__qmd__vector_search, mcp__qmd__deep_search, mcp__qmd__get, mcp__qmd__multi_get
argument-hint: "[question about knowledge systems or methodology]"

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 maintenan
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Ships witharscontexta

A second brain for your agent. A Claude Code plugin that generates complete knowledge systems from conversation. You describe how you think and work.

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Repo: agenticnotetaking/arscontexta

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