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by swisspra
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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memory_token_usage

Read-onlyIdempotent

Check token usage breakdown across memory components and get compaction recommendations to keep context within limits.

Instructions

Show token usage breakdown and recommend compaction if needed.

Returns token estimates for: hot memories, digests, archive, briefing output.

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": "memory_token_usage"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.0.4

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is clear. The description adds behavior beyond the annotations by stating the tool makes a compaction recommendation and lists the specific token estimate categories (hot memories, digests, archive, briefing output), providing useful 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?

The description is two concise sentences, front-loaded with the main action. It avoids redundancy and every sentence provides distinct value—the second sentence details what the breakdown includes.

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

Completeness5/5

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

Given the tool's simplicity (no params), the existing output schema, and annotations covering safety, the description provides sufficient context. It mentions the categories of token estimates and the recommendation function, making the tool's purpose and output clear without needing further elaboration.

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 description carries no parameter burden. Per the baseline for 0 params, a score of 4 is appropriate.

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 uses a specific verb ('Show') and resource ('token usage breakdown') and adds an additional behavior ('recommend compaction if needed'). This clearly distinguishes it from sibling tools like memory_compact (which performs compaction) and memory_status (which likely provides general status).

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?

The description implies when to use the tool (when token usage needs assessment or compaction may be needed) but does not explicitly state when to use it over alternatives like memory_status or memory_compact. No exclusions or alternative tool references are provided.

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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