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query_usage

Retrieve monthly call volume, downstream traffic, average latency, and endpoint-level statistics for the current month or a specified YYYY-MM.

Instructions

用量统计：查询自己当月（或指定 YYYY-MM）的调用量/下行流量/平均耗时与分端点统计。

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": "query_usage"
  }
}

Input Schema

Name	Required	Description	Default
`month`	No	YYYY-MM，缺省当月

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations, the description carries the full disclosure burden. It usefully scopes the query to the caller's own usage ('自己') and lists the four metric categories returned, which is valuable given there is no output schema. It does not state auth requirements, rate limits, or whether results are paginated for high-volume accounts.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single compact sentence, front-loaded with the tool's purpose (用量统计) followed by the metric list. No filler or repetition. Slightly dense with the parenthetical month clause embedded mid-sentence, but nothing is wasted.

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 simple read-only tool with one optional parameter and no output schema, the description is nearly sufficient: it identifies scope, the default period, and the returned metrics. Only the ambiguity of what '自己' resolves to (API key, account, or workspace) and any response-shape details are left unstated.

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

Parameters3/5

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

Schema description coverage is 100% and the single parameter already documents 'YYYY-MM，缺省当月'. The description merely restates the same default, adding no format rules, range limits, or error behavior beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 names a specific verb (查询/统计) and resource (用量), and enumerates exactly what is measured: 调用量、下行流量、平均耗时与分端点统计. This is far more specific than the bare name query_usage. It does not differentiate against siblings, but no sibling tool overlaps in domain, so differentiation is unnecessary rather than missing.

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 phrase '自己当月（或指定 YYYY-MM）' implies the usage context: call it with no argument for the current month, or pass a month to target a specific period. However, there is no explicit when-to-use vs alternatives, no prerequisites, and no stated exclusions. Usage is implied rather than guided.

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