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n24q02m

Mnemo - Persistent AI Memory

by n24q02m
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

search_memory

Read-only

Find existing memories with natural language queries, preventing duplicates when adding new information.

Instructions

Find existing memories by natural language query. Always search before adding.

ACTION GUIDE — when to use:

  • Use BEFORE adding new information to avoid duplicates. Example: query='dark mode preference'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
limitNo
queryYes
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv2.6.0
    • addedOutput schema / additionalProperties
      Added value: +true
    • removedOutput schema / properties
      Removed value: -{
-  "result": {
-    "title": "Result",
-    "type": "string"
-  }
-}
    • removedOutput schema / required
      Removed value: -[
-  "result"
-]
    • changedOutput schema / title
      Previous value: -"search_memoryOutput"New value: +"search_memoryDictOutput"
  2. Addedv2.1.1

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. Description adds that it uses natural language query and is for pre-addition search, but doesn't detail other behavioral aspects.

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?

Two sentences, front-loaded with purpose and usage guidance, no wasted words. Every part earns its place.

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?

With 4 parameters and 0% schema description coverage, the description does not address parameter details or output structure (though output schema exists). Lacks completeness for a search tool with multiple optional fields.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not explain any parameters (e.g., tags, limit, category format). The only reference is to 'query' implicitly. Fails to compensate for minimal schema documentation.

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 'Find existing memories by natural language query', specifying verb and resource. It distinguishes itself from siblings like add_memory by emphasizing search before adding.

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?

Explicitly instructs to use 'BEFORE adding new information to avoid duplicates', with an example. Does not explicitly name alternatives but provides clear contextual guidance.

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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