Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/kmshihab7878/claude-code-setup --skill understand-coremindAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
/understand-coremind
Query the CoreMind knowledge graph with governance-aware context. This skill understands the GAOS architecture, agent hierarchy, and 10-stage pipeline.
Instructions
- Load the knowledge graph from
CoreMind/.understand-anything/knowledge-graph.json - Parse the query from
$ARGUMENTSand 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)
| Layer | Nodes | Key Components |
|---|---|---|
| Orchestration Core | 276 | CoreMind, Planner, PolicyGate, IntentParser, GoalLedger, DelegationEngine |
| Agent Framework | 236 | BaseAgent, executives (CEO/CTO/CFO/CMO/COO), tools, capabilities |
| Integration Layer | 454 | FastAPI routes, middleware, connectors, interfaces, billing |
| Governance & Safety | 146 | GAOS (5-layer safety), security (RBAC, JWT, hash chain, audit) |
| Knowledge & Learning | 127 | RAG pipeline, knowledge store, evaluation benchmarks |
| Data & Persistence | 181 | SQLAlchemy models (15 entity types), repositories |
| Presentation | 436 | Next.js frontend, 5 product surfaces (Forge, Helios, Nova, Command, Studio) |
| Cross-Cutting | 55 | LLM providers (OpenAI, Anthropic, Ollama, Kimi), model router |
Response Format
Always include:
- Direct answer to the query
- Graph context: which nodes/layers are relevant
- Governance implications: does this touch governance/safety layers?
- Suggestion: related areas to explore or commands to run (
/understand-explain,/understand-chat)
