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Sales, refunds and revenue

get_sales
Read-onlyIdempotent

Units sold, units returned (refunds), gross, tax and net revenue in USD, for one game or the whole account. Group by day, week, month or total, and break down by country, discount level, package or app. Refund rate per row. Days are Pacific time, as Valve reports them.

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": "get_sales"
  }
}

Input Schema

NameRequiredDescriptionDefault
appidNoSteam app id; omit for every app on the account
limitNoRows to return
countryNoTwo-letter country code, e.g. US, DE, CN
end_dateNoLast day, YYYY-MM-DD. Default: the newest day with data (yesterday)
group_byNototal
breakdownNonone
start_dateNoFirst day, YYYY-MM-DD. Default: 28 days before end_date

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely non-obvious context: revenue is in USD, a refund rate is computed per row, and day boundaries follow Pacific time as Valve reports them. It stops short of describing row-limit or aggregation behavior on the return side, but the added semantics are real.

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 dense sentences, front-loaded with the metrics and then the shaping options, with zero filler. Every clause conveys either what is returned or how to slice it.

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?

With seven optional parameters, no output schema, and partial schema coverage, the description does the important work of enumerating the return metrics and clarifying timezone and currency. It leaves limit/row-count semantics and pagination to the schema, which is acceptable since those fields are documented there.

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?

Schema coverage is 71%, and the two enum parameters (group_by, breakdown) have no schema descriptions at all, so the description carries them: it enumerates day/week/month/total and country/discount/package/app in readable terms. It also reinforces the appid-omitted-means-whole-account rule and the USD unit, adding meaning beyond the schema for the weakest-documented fields.

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 the exact metrics returned (units sold, units returned/refunds, gross, tax, net revenue in USD) and the scope (one game or whole account), which clearly separates it from wishlist, event, and account-status siblings. The verb is only implied by the tool name rather than stated, so it falls just short of a full 5.

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?

It gives useful framing on how to shape the query (group by day/week/month/total, break down by country/discount/package/app) and states the appid scope rule. However, it never says when to prefer this tool over alternatives such as get_event_impact or compare_titles, and gives no exclusions or prerequisites.

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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