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From cortex
Traverses the knowledge graph to trace entity relationships, causal chains, co-access paths, and memory clusters. Use when exploring connections between concepts or drilling into related memories.
npx claudepluginhub cdeust/cortex --plugin cortexHow this skill is triggered — by the user, by Claude, or both
Slash command
/cortex:cortex-navigate-knowledgeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
knowledge graph, relationships, connections, causal chain, how are these related, what connects, drill down, explore, navigate, entity graph, trace, cause and effect, related to, linked to, co-access, cluster
Traverses knowledge graph across memories, entities, and relationships for comprehensive context. Use before planning complex work, investigating concept connections, or answering 'what do you know about X'.
Use when user asks "what do you know about X", when planning complex work that spans multiple topics, when investigating how concepts connect across projects, or when simple memory queries don't provide enough context. Deep traversal of Forgetful MCP knowledge graph (mcp__forgetful__* tools).
Searches, traverses, and narrates connections in a knowledge graph to surface what's known and what's missing about a topic.
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knowledge graph, relationships, connections, causal chain, how are these related, what connects, drill down, explore, navigate, entity graph, trace, cause and effect, related to, linked to, co-access, cluster
Cortex maintains a knowledge graph of entities (people, technologies, concepts, files) and their relationships extracted from memories. This skill lets you traverse that graph — follow causal chains, explore co-access patterns, drill into fractal memory clusters, and understand how different pieces of knowledge connect.
Use this skill when: You need to understand relationships between concepts, trace cause-and-effect chains, or explore a topic area systematically.
Follow entity relationships through the knowledge graph:
cortex:get_causal_chain({
"entity": "PostgreSQL",
"direction": "both",
"max_depth": 3
})
Returns a chain of entities connected by typed relationships (causes, uses, depends_on, related_to, etc.). Direction can be "forward" (effects), "backward" (causes), or "both".
Find memories frequently accessed together using Successor Representation:
cortex:navigate_memory({
"memory_id": <starting_memory_id>,
"depth": 2,
"max_nodes": 20
})
Returns a graph of memories connected by co-access frequency — revealing implicit relationships that aren't in the explicit knowledge graph.
Browse memories through fractal clusters (L0 = broad, L1 = mid, L2 = specific):
cortex:recall_hierarchical({
"query": "authentication system",
"levels": 3
})
Then drill into any interesting cluster:
cortex:drill_down({
"cluster_id": "<cluster from hierarchical recall>",
"level": "L1"
})
Find disconnected or under-connected areas:
cortex:detect_gaps({
"domain": "<optional>"
})
Returns isolated entities, sparse domains, and temporal drift — areas where your knowledge graph has holes.
Understanding a new codebase:
Debugging with context:
Architecture review: