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).
Deep traverses Forgetful MCP knowledge graph to uncover interconnected context when exploring topics, planning complex work, or investigating concept relationships across projects. Uses phased expansion from semantic entry points through entity relationships to reveal comprehensive context beyond simple memory queries.
/plugin marketplace add ScottRBK/context-hub-plugin/plugin install context-hub-plugin@forgetful-pluginsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Forgetful stores knowledge as an interconnected graph: memories link to other memories, entities link to memories, and entities relate to each other. Deep exploration reveals context that simple queries miss.
Explore the knowledge graph when:
Track visited IDs to prevent cycles. Execute phases sequentially.
execute_forgetful_tool("query_memory", {
"query": "<topic>",
"query_context": "Exploring knowledge graph for comprehensive context",
"k": 5,
"include_links": true,
"max_links_per_primary": 5
})
Collect: primary_memories + linked_memories (1-hop connections).
For key memories, get full details:
execute_forgetful_tool("get_memory", {"memory_id": <id>})
Extract: document_ids, code_artifact_ids, project_ids, additional linked_memory_ids.
Find entities in discovered projects:
execute_forgetful_tool("list_entities", {
"project_ids": [<discovered project ids>]
})
For relevant entities, map relationship graph:
execute_forgetful_tool("get_entity_relationships", {
"entity_id": <id>,
"direction": "both"
})
Relationship types: works_for, owns, manages, collaborates_with, etc.
For each entity, find all linked memories:
execute_forgetful_tool("get_entity_memories", {
"entity_id": <id>
})
Returns {"memory_ids": [...], "count": N}. Fetch any new memories not already visited.
Group findings by type:
Memories: Primary (direct matches) → Linked (1-hop) → Entity-linked (via entities)
Entities: Name, type, relationship count, linked memory count
Artifacts: Documents and code snippets found via memory links
Graph Summary: Total nodes, key themes, suggested follow-up queries
Match depth to task complexity. Start shallow, go deeper if context insufficient.
truncated flag from query_memory (8000 token budget)project_ids filter to scope explorationCreate employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
Implement GDPR-compliant data handling with consent management, data subject rights, and privacy by design. Use when building systems that process EU personal data, implementing privacy controls, or conducting GDPR compliance reviews.