/kg
Knowledge graph operations — extract entities, traverse relations, and search the graph
> /plugin marketplace add ruvnet/ruflo
Command definition
kg.mdname: kg
description: Knowledge graph operations — extract entities, traverse relations, and search the graph
Knowledge graph commands:
**`kg extract <path>`** -- Extract entities and relations from source files at the given path. 1. Scan files at `<path>` recursively for classes, functions, modules, types, and config references 2. For each entity, record its type, name, file location, and description 3. Map relations between entities: imports, extends, implements, depends-on, calls, references 4. Store entities via `mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store` in the `knowledge-graph` namespace 5. Create causal edges via `mcp__plugin_ruflo-core_ruflo__agentdb_causal-edge` for each relation 6. Report: total entities found, total relations mapped, entity type breakdown
**`kg traverse <entity>`** -- Pathfinder traversal starting from the named entity. 1. Look up the seed entity via `mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall` 2. Expand outward by following causal edges (default depth: 3) 3. Score each path: `relevance = edge_weight * semantic_similarity(query, node)` 4. Prune paths with cumulative score below 0.3 5. Return the top 10 paths with entities, relations, and scores
**`kg relations <entity>`** -- List all direct relations for the named entity. 1. Query causal edges where source or target matches `<entity>` 2. Group by relation type (imports, extends, implements, depends-on, calls) 3. Display as a table with: relation, direction (incoming/outgoing), target entity, weight
**`kg visualize`** -- Generate an ASCII visualization of the knowledge graph. 1. Recall all entities and edges from the `knowledge-graph` namespace 2. Identify the most-connected nodes (top 10 by degree) 3. Render a simplified graph showing key nodes and their connections 4. Include legend with entity types and relation types
**`kg search <query>`** -- Semantic search across the knowledge graph. 1. Search entities via `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search` (the `semanticRouter` controller is `enabled: false` in current AgentDB builds — pattern-search is the available substitute; see ruvnet/ruflo#2049) 2. Expand results with causal edges to show related context 3. Rank by pattern-match score (fall back to `mcp__plugin_ruflo-core_ruflo__embeddings_generate` + manual cosine for higher-fidelity semantic similarity if needed) 4. Display matches with entity name, type, file location, and relevance score
Read more
name: kg description: Knowledge graph operations — extract entities, traverse relations, and search the graph
Knowledge graph commands:
**`kg extract <path>`** -- Extract entities and relations from source files at the given path. 1. Scan files at `<path>` recursively for classes, functions, modules, types, and config references 2. For each entity, record its type, name, file location, and description 3. Map relations between entities: imports, extends, implements, depends-on, calls, references 4. Store entities via `mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store` in the `knowledge-graph` namespace 5. Create causal edges via `mcp__plugin_ruflo-core_ruflo__agentdb_causal-edge` for each relation 6. Report: total entities found, total relations mapped, entity type breakdown
**`kg traverse <entity>`** -- Pathfinder traversal starting from the named entity. 1. Look up the seed entity via `mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall` 2. Expand outward by following causal edges (default depth: 3) 3. Score each path: `relevance = edge_weight * semantic_similarity(query, node)` 4. Prune paths with cumulative score below 0.3 5. Return the top 10 paths with entities, relations, and scores
**`kg relations <entity>`** -- List all direct relations for the named entity. 1. Query causal edges where source or target matches `<entity>` 2. Group by relation type (imports, extends, implements, depends-on, calls) 3. Display as a table with: relation, direction (incoming/outgoing), target entity, weight
**`kg visualize`** -- Generate an ASCII visualization of the knowledge graph. 1. Recall all entities and edges from the `knowledge-graph` namespace 2. Identify the most-connected nodes (top 10 by degree) 3. Render a simplified graph showing key nodes and their connections 4. Include legend with entity types and relation types
**`kg search <query>`** -- Semantic search across the knowledge graph. 1. Search entities via `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search` (the `semanticRouter` controller is `enabled: false` in current AgentDB builds — pattern-search is the available substitute; see ruvnet/ruflo#2049) 2. Expand results with causal edges to show related context 3. Rank by pattern-match score (fall back to `mcp__plugin_ruflo-core_ruflo__embeddings_generate` + manual cosine for higher-fidelity semantic similarity if needed) 4. Display matches with entity name, type, file location, and relevance score
📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification. Agent = Model + Harness.
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