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Mnemonic

Mnemonic

by bacharyehya
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

mnemonic_export

Export all active memories to a JSON file for backup, transfer between systems, or debugging. Provides a complete snapshot that can be imported later.

Instructions

Export all active memories to JSON.

Returns a complete export that can be imported later or backed up. Useful for:

  • Backing up memories

  • Transferring to another system

  • Debugging

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "mnemonic_export"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It states the export covers 'all active memories' and is 'complete', implying a read-only operation without side effects, but does not explicitly state non-destructiveness, authentication requirements, or potential limitations like size. This is adequate but not thorough.

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 concise, front-loaded with the main purpose, and uses a clear bullet list for use cases. Every sentence adds value without redundancy or fluff.

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

Completeness4/5

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

Given the tool's simplicity (no parameters), the presence of an output schema, and a clear description of purpose and when to use it, the description is fairly complete. The main gap is the lack of safety/behavioral details, but since it is a simple export operation, the provided information is sufficient for most use cases.

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 zero parameters and the schema coverage is 100%, so there are no parameter semantics to explain. Baseline 4 is appropriate; the description adds value by clarifying what the export contains (all active memories) rather than focusing on 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?

Description clearly states the tool exports all active memories to JSON, using a specific verb ('Export') and resource ('all active memories'). It distinguishes from siblings by specifying the export format and scope, making it distinct from mnemonic_list or mnemonic_get.

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

Usage Guidelines4/5

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

Provides explicit use cases: backing up memories, transferring to another system, and debugging. This gives clear context for when to use the tool, though it does not explicitly mention when not to use it or name alternative tools as exclusions.

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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