DoubleData MCP

Export usage report

export_usage

Idempotent

Download a per-credential usage report as CSV or JSON to the local export directory for saving or sharing traffic data as a file or spreadsheet.

Instructions

Download a per-credential usage report as CSV or JSON into the local export directory. Use when the user wants a file, spreadsheet or report of their traffic.

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": "export_usage"
  }
}

Input Schema

Name	Required	Description	Default
`to`	No	Exclusive UTC end date (YYYY-MM-DD). Must be 1 to 366 days after from.
`from`	No	Inclusive UTC start date (YYYY-MM-DD). Defaults to the current UTC month.
`path`	No	Relative file path inside the export directory.
`format`	No		csv
`username`	No	Limit the report to one proxy credential username.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 9, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already declare the safety profile (destructiveHint=false, idempotentHint=true, openWorldHint=true), and readOnlyHint=false is consistent with writing a local file even though the name implies reading. The description usefully adds where the artifact lands (local export directory), but says nothing about overwriting an existing file at a given path, whether directories are created, or what the call returns.

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?

Two sentences, zero padding, with the primary action and output shape front-loaded before the when-to-use cue. Every clause carries information.

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?

Five optional parameters with strong schema coverage and no output schema, so the description does not need to explain fields. It covers action, format and destination, but leaves the return value ambiguous — an agent cannot tell whether it receives a file path, a confirmation, or file contents.

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 coverage is 80%, so the schema already documents the date bounds and formats; the description only echoes format choice and the per-credential scope. It adds no semantics for 'path' (overwrite behavior, subdirectory handling) beyond what the schema field says.

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?

Names a specific verb (download) and resource (per-credential usage report) plus the output formats (CSV/JSON) and destination (local export directory). This distinguishes it from the read-style sibling get_usage, though the description never names that sibling explicitly, so the contrast must be inferred from 'file' vs. inline data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use when the user wants a file, spreadsheet or report of their traffic' gives a clear triggering condition tied to the desired output artifact rather than the data itself. It stops short of naming get_usage as the alternative for inline/non-file queries and states no exclusions.

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