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T1nker-1220

Knowledge Graph Memory Server

read_graph

Retrieve the complete knowledge graph to access stored information and learned lessons from previous interactions.

Instructions

Read the entire knowledge graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core handler function for reading the entire knowledge graph by delegating to loadGraph(). This is the main logic executed by the tool.
    async readGraph(): Promise<KnowledgeGraph> {
      return this.loadGraph();
    }
  • index.ts:1062-1069 (registration)
    Registration of the 'read_graph' tool in the list returned by ListToolsRequestHandler, including name, description, and empty input schema.
    {
      name: "read_graph",
      description: "Read the entire knowledge graph",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
  • Dispatch handler in CallToolRequestSchema that executes the read_graph tool by calling knowledgeGraphManager.readGraph() and returning JSON-formatted response.
    case "read_graph":
      return { content: [{ type: "text", text: JSON.stringify(await knowledgeGraphManager.readGraph(), null, 2) }] };
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Read' which implies a read-only operation, but doesn't specify aspects like whether it returns all nodes/relations, potential performance impacts for large graphs, or error conditions. This leaves significant gaps for a tool that presumably accesses a knowledge graph.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately understandable without any fluff or redundancy.

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

Completeness2/5

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

Given the complexity of reading a knowledge graph, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'entire' means (e.g., all nodes, relations, metadata), the return format, or any limitations, which are critical for an AI agent to use this tool effectively.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for 0 parameters is 4, as it avoids unnecessary detail while matching the schema.

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 action ('Read') and resource ('the entire knowledge graph'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'search_nodes' or 'open_nodes' that might also involve reading graph data, so it misses full sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'search_nodes' and 'open_nodes' that might offer more targeted reading, there's no indication of when this tool is preferred (e.g., for comprehensive retrieval vs. filtered queries).

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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