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memory

memory

by harsh-gulhane
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_stats

Retrieve an overview of stored memories, including totals, category and importance breakdowns, top entities, active threads, and expired counts.

Instructions

Get overview stats: total memories, breakdown by category, importance, top entities, active threads, expired count.

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": "get_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations, so the description carries the burden. 'Get' implies a safe read and the enumerated outputs hint at an aggregate scan over the whole store, but it doesn't state scope (all memories?), cost, or that nothing is mutated. Adequate but not rich behavioral context.

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?

One front-loaded sentence with a compact, comma-separated inventory of the returned aggregates. No filler, no repetition of the tool name.

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?

With an output schema present and no parameters, the description only needed to signal scope and content, which it does. Minor gap: it doesn't say the stats cover the entire memory store versus a filtered subset, which would matter for interpretation.

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?

Zero parameters, which is the baseline-4 case; the description correctly implies no input is needed to scope the call. Nothing more is required on this dimension.

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?

States a specific verb (get) and resource (overview stats), then enumerates the exact aggregates returned: totals, category/importance breakdowns, top entities, threads, expired count. This clearly distinguishes it from CRUD siblings like list_memories or search_memory, though it never explicitly says 'read-only aggregate'.

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?

Usage is only implied — an agent can infer this is the dashboard/overview entry point rather than a filtered query. No explicit when-to-use versus alternatives (e.g., get_daily_summary, list_memories) or exclusions are given.

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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