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Usage summary

usage_summary
Read-onlyIdempotent

Totals for a meter: event count, total quantity, accrued minor units.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "meter_id": "<meter_id>"
    },
    "name": "usage_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
meter_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and non-destructive, so safety behavior is covered without description help. The description adds that the result is an aggregate rollup rather than raw events, which is useful behavioral context. It stops short of saying what aggregation window is totaled, which is the key unknown for a summary tool.

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?

A single, front-loaded sentence with no filler; the returned metrics are listed immediately and nothing is wasted.

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

Completeness3/5

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

The tool is simple (one required parameter, output schema present, read-only annotations), so much of the burden is already carried elsewhere. Still, the description omits the aggregation period covered by the totals, which is material for interpreting the numbers, and leaves meter_id undocumented.

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 single parameter meter_id has no documentation in either the schema or the description. The phrase 'for a meter' only loosely implies that meter_id identifies the meter being totaled; it adds no format, prefix, or lookup guidance to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource (a meter) and enumerates the specific outputs (event count, total quantity, accrued minor units), so an agent knows roughly what it returns. However, it never states the action verb (retrieve/aggregate) and does not distinguish itself from the sibling usage_timeseries, which plausibly returns overlapping aggregate data. Purpose is implied rather than stated.

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?

There is no when-to-use guidance, no precondition, and no mention of the obvious alternative usage_timeseries. The agent must infer the selection rule from the tool name alone.

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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