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yodakeisuke

Knowledge Graph Memory Server

by yodakeisuke

open_nodes

Retrieve complete information from the knowledge graph by specifying entity names to access stored data including subdomains and metadata.

Instructions

Open specific nodes in the knowledge graph by their names. Returns the complete node information including subdomain and all metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namesYesAn array of entity names to retrieve, returning full entity information including subdomain

Implementation Reference

  • The core handler function that implements the 'open_nodes' tool logic. It loads the knowledge graph, filters entities by the provided names, finds connecting relations, and returns the subgraph.
    async openNodes(names: string[]): Promise<KnowledgeGraph> {
      const graph = await this.loadGraph();
      
      const filteredEntities = graph.entities.filter(e => names.includes(e.name));
    
      const filteredEntityNames = new Set(filteredEntities.map(e => e.name));
    
      const filteredRelations = graph.relations.filter(r => 
        filteredEntityNames.has(r.from) && filteredEntityNames.has(r.to)
      );
    
      return {
        entities: filteredEntities,
        relations: filteredRelations,
      };
    }
  • index.ts:522-536 (registration)
    Registers the 'open_nodes' tool in the list of tools returned by ListToolsRequest, including its name, description, and input schema.
    {
      name: "open_nodes",
      description: "Open specific nodes in the knowledge graph by their names. Returns the complete node information including subdomain and all metadata.",
      inputSchema: {
        type: "object",
        properties: {
          names: {
            type: "array",
            items: { type: "string" },
            description: "An array of entity names to retrieve, returning full entity information including subdomain",
          },
        },
        required: ["names"],
      },
    },
  • Defines the input schema for the 'open_nodes' tool, specifying an object with a required 'names' array of strings.
    inputSchema: {
      type: "object",
      properties: {
        names: {
          type: "array",
          items: { type: "string" },
          description: "An array of entity names to retrieve, returning full entity information including subdomain",
        },
      },
      required: ["names"],
    },
  • The dispatch case in the CallToolRequest handler that invokes the openNodes method on the knowledgeGraphManager instance.
    case "open_nodes":
      return createResponse(JSON.stringify(await knowledgeGraphManager.openNodes(args.names as string[]), null, 2));
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses the behavior of returning 'complete node information including subdomain and all metadata', which adds value beyond the input schema. However, it doesn't cover error handling (e.g., invalid names), performance aspects (e.g., rate limits), or mutation effects (implied read-only but not stated). The description is adequate but misses key operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences: the first states the action and input, the second specifies the output. Every word earns its place with no redundancy or fluff. It's front-loaded with the core purpose and efficiently structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 1 parameter with 100% schema coverage and no output schema, the description is moderately complete. It covers purpose and output but lacks details on errors, permissions, or performance. For a read operation with no annotations, it should ideally mention safety (non-destructive) or limitations, but it's adequate for basic use. The absence of an output schema increases the burden slightly, which isn't fully met.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the 'names' parameter fully documented in the schema as 'An array of entity names to retrieve, returning full entity information including subdomain'. The description adds marginal value by reinforcing 'by their names' and linking to the output, but doesn't provide additional syntax, constraints, or examples beyond the schema. Baseline 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Open specific nodes in the knowledge graph by their names' (verb+resource) and 'Returns the complete node information including subdomain and all metadata' (outcome). It distinguishes from siblings like 'search_nodes' (search vs. open by name) and 'read_graph' (read entire graph vs. specific nodes), though not explicitly named. However, it doesn't fully differentiate from 'search_nodes' in edge cases where names are known.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you know exact node names ('by their names') and want complete information. It doesn't explicitly state when to use alternatives like 'search_nodes' (for fuzzy/partial matches) or 'read_graph' (for entire graph), nor does it mention prerequisites or exclusions. The context is clear but lacks explicit guidance on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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