kmshihab7878/claude-code-setup

understand-coremind

CoreMind specific knowledge graph queries with governance-aware layer mapping and agent hierarchy understanding

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How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/kmshihab7878/claude-code-setup --skill understand-coremind

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

/understand-coremind

Query the CoreMind knowledge graph with governance-aware context. This skill understands the GAOS architecture, agent hierarchy, and 10-stage pipeline.

Instructions

  1. Load the knowledge graph from CoreMind/.understand-anything/knowledge-graph.json
  2. Parse the query from $ARGUMENTS and determine query type:

Query Types

Architecture queries ("how does X work", "what is the pipeline", "explain governance"):

  • Map the query to relevant layers and nodes in the graph
  • Explain using the orchestrator governance model:
  • 10-stage pipeline: IntentParser -> PolicyGate -> GoalLedger -> Planner -> DelegationEngine -> AgentCoordinator -> ReflectionLoop -> OutcomeTracker -> WorldState
  • 4-tier governance: ALLOW (auto-approve) / REVIEW (human check) / ESCALATE (multi-agent review) / BLOCK (deny)
  • 5-layer safety stack: Input sanitization -> Policy gate -> Execution sandbox -> Output validation -> Recovery

Agent queries ("which agents handle X", "what does the CEO agent do"):

  • Search the Agent Framework layer (236 nodes)
  • Map agent hierarchy: L0 System Core -> L1 Executives (CEO/CTO/CFO/CMO/COO) -> L2+ Specialists
  • Include agent capabilities, tools, and delegation patterns

Module queries ("what does the API layer do", "how does knowledge store work"):

  • Search the relevant architecture layer
  • Include: module purpose, file count, key components, dependencies (from module edges)
  • Cross-reference with Memory MCP entities: mcp__memory__search_nodes("CoreMind:Module:{name}")

Impact queries ("what would break if I change X", "dependencies of core_mind"):

  • Find the target node in the graph
  • Traverse 1-hop edges (imports, calls, inherits, depends_on)
  • Identify cross-layer impact
  • Rate risk: LOW (same layer) / MEDIUM (adjacent layers) / HIGH (3+ layers affected)

Tour queries ("give me the tour", "where do I start"):

  • Return the 15-step guided tour from the knowledge graph
  • Each step: title, node, description, why it matters

CoreMind Architecture Layers (8)

LayerNodesKey Components
Orchestration Core276CoreMind, Planner, PolicyGate, IntentParser, GoalLedger, DelegationEngine
Agent Framework236BaseAgent, executives (CEO/CTO/CFO/CMO/COO), tools, capabilities
Integration Layer454FastAPI routes, middleware, connectors, interfaces, billing
Governance & Safety146GAOS (5-layer safety), security (RBAC, JWT, hash chain, audit)
Knowledge & Learning127RAG pipeline, knowledge store, evaluation benchmarks
Data & Persistence181SQLAlchemy models (15 entity types), repositories
Presentation436Next.js frontend, 5 product surfaces (Forge, Helios, Nova, Command, Studio)
Cross-Cutting55LLM providers (OpenAI, Anthropic, Ollama, Kimi), model router

Response Format

Always include:

  1. Direct answer to the query
  2. Graph context: which nodes/layers are relevant
  3. Governance implications: does this touch governance/safety layers?
  4. Suggestion: related areas to explore or commands to run (/understand-explain, /understand-chat)

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