Explore a knowledge graph, a network of entities and relationships, from a chosen starting point. Rank relevant paths and summarize dependencies or indirect connections to help understand code structure and assess the impact of changes.
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Pathfinder traversal of the knowledge graph starting from a seed entity
安装前可以查看交给 AI 代理的指令内容。
Perform pathfinder graph traversal starting from a seed entity. Expands outward through the graph's edges, scores paths by relevance, and prunes low-scoring branches.
When you need to explore the knowledge graph starting from a specific entity -- finding what depends on it, what it depends on, or discovering indirect relationships. Useful for impact analysis, dependency chains, and understanding code structure.
mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall to look up the target entity by name (one word is the most reliable query: the recall matches the whole query as a substring). Graph node ids are domain-prefixed, for example entity:router-account.mcp__plugin_ruflo-core_ruflo__agentdb_graph-query with { nodeId: "entity:NAME", mode: "k-hop", depth: N } (default depth 3, the SQL path applies at most 3 and reports appliedDepth and truncated; add relation to filter by relation type). agentdb_causal-edge only records an edge, never use it to read one.mcp__plugin_ruflo-core_ruflo__agentdb_graph-pathfinder with { seedNodeId: "entity:NAME", query: "<what the user wants to know>", depth: N, threshold: 0.3, topK: 10 }. It expands from the seed, scores each path by cumulative relevance, drops paths under the threshold and returns the top paths. If it returns nothing useful, score the k-hop neighbours yourself with mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search on entity names and relation types (the semanticRouter controller is enabled: false in current AgentDB builds; see ruvnet/ruflo#2049).agentdb_context-synthesize: it summarizes validated task episodes and answers no-eligible-episodes for entity records written by kg-extract.With CLAUDE_FLOW_ENCRYPT_AT_REST=1 the graph read tools answer graph_edges DB is encrypted at rest (RFE1) (#2889, #4135): edges recorded by kg-extract are stored but cannot be read back yet. Say so in the report. Your data is intact: do not run memory init. Fall back to the entity records only (agentdb_hierarchical-recall) and tell the user that relations are unavailable. An agentdb_causal-edge result with readable: false already warns about this at write time.
npx @claude-flow/cli@latest memory search --query "relations for ENTITY_NAME" --namespace knowledge-graph
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Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
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Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
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Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
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Rebuild the index of ADRs, records of architectural decisions, after files or relationship lines are deleted. It clears stored records and relationships, indexes the files still present, and checks that the final record count matches.
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Review code changes against accepted Architecture Decision Records, documents that capture agreed design choices. Report violations, outdated references, compliant changes, and areas without ADR coverage, then suggest code fixes or a new decision record where appropriate.
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Check saved architecture decision records (ADRs) for broken references, circular replacement relationships, and inconsistent statuses. Use the results to verify imported records or stop a CI check when selected integrity rules fail.
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