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Glama

memory_stats

Retrieve statistics across facts, payloads, decisions, workflows, aliases, and relations to monitor memory usage and support governance of AI agent memory.

Instructions

Get memory statistics across facts, payloads, decisions, workflows, aliases, and relations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.9.1

TDQS

B3.3/5.0
Behavior2/5

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

There are no annotations, and the description only says 'Get memory statistics,' which implies a read operation but provides no details on whether the computation is expensive, whether results are cached, or what specific statistical measures are returned. The description adds little beyond the tool name and does not carry the behavioral disclosure burden.

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, front-loaded sentence with no filler. Every word contributes to specifying the verb, resource, and scope, making it easy to parse quickly.

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?

For a zero-parameter tool with an output schema, the description is largely complete: it states the resource and the categories covered. However, it lacks any contextual hint about how this differs from the memory_health or memory_list tools, leaving a small but real completeness gap.

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, so the baseline is 4. The description adds value by enumerating the data categories covered by the statistics, which helps an agent understand the scope of the result even though no arguments are needed.

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 uses a specific verb ('Get') and identifies the resource ('memory statistics') with an explicit category list: facts, payloads, decisions, workflows, aliases, and relations. It is clear what the tool does, though it does not explicitly distinguish itself from memory_health or the various memory_list siblings.

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?

No guidance is provided about when to use this tool versus alternatives such as memory_health or memory_list. An agent must infer that this is a roll-up statistics tool rather than a subscription or health check, which leaves usage context unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.