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show_memory_path

Retrieve the absolute path of the active knowledge-graph file to enable structured reasoning and persistent memory access for AI assistants in complex problem-solving tasks.

Instructions

Return absolute path of the active knowledge-graph file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
random_stringNoDummy parameter for no-parameter tools

Implementation Reference

  • The tool handler function that returns the JSON-stringified path to the memory file, using the MEMORY_PATH environment variable or a default path in the user's home directory.
    execute: async (_args, { log }) => {
      const memoryPath = process.env.MEMORY_PATH || path.join(os.homedir(), '.mcp-think-tank/memory.jsonl');
      // Removed debug log
      return JSON.stringify(memoryPath);
    }
  • Zod schema defining the optional dummy input parameter for the tool.
    parameters: z.object({
      random_string: z.string().describe("Dummy parameter for no-parameter tools").optional()
    }),
  • Registration of the show_memory_path tool in the registerUtilityTools function.
    server.addTool({
      name: 'show_memory_path',
      description: 'Return absolute path of the active knowledge-graph file.',
      parameters: z.object({
        random_string: z.string().describe("Dummy parameter for no-parameter tools").optional()
      }),
      execute: async (_args, { log }) => {
        const memoryPath = process.env.MEMORY_PATH || path.join(os.homedir(), '.mcp-think-tank/memory.jsonl');
        // Removed debug log
        return JSON.stringify(memoryPath);
      }
    });
  • Invocation of registerUtilityTools during overall tool registration, which includes show_memory_path.
    registerUtilityTools(server);
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns a path but doesn't clarify if this is a read-only operation, whether it requires specific permissions, or what happens if no active file exists. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 that front-loads the core purpose without any wasted words. It directly communicates what the tool does in a clear and structured manner, making it easy to parse quickly.

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 the tool's simplicity (no functional parameters, no output schema, no annotations), the description is adequate but minimal. It explains the basic purpose but lacks context about the knowledge-graph system, error conditions, or return format, which could help an agent use it more effectively in complex scenarios.

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 tool has 0 required parameters and 1 dummy parameter with 100% schema description coverage, so the schema fully documents the input structure. The description appropriately adds no parameter details, as none are needed, aligning with the baseline for zero functional parameters.

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

Purpose5/5

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

The description clearly states the specific action ('Return absolute path') and the resource ('active knowledge-graph file'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'read_graph' or 'memory_query' by focusing solely on file path retrieval rather than content manipulation or querying.

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 like 'read_graph' or 'memory_query', nor does it mention prerequisites or exclusions. It lacks context about the active knowledge-graph file's role in the system, leaving usage entirely implicit.

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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