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by net.crawlora
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datasets_steam_playercounts_facets

Read-only

Return up to 50 facet buckets with counts for one Steam player-count field using the filters from datasets_steam_playercounts_search. facet accepts app_id or snapshot_date; page and page_size do not change counts; sort is validated but does not change bucket order. Supplying date scopes the snapshot-date counts to that date. Use datasets_steam_playercounts_search to find daily records.

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": {
      "facet": "<facet>"
    },
    "name": "datasets_steam_playercounts_facets"
  }
}

Input Schema

NameRequiredDescriptionDefault
dateNoOptional snapshot date filter, yyyy-MM-dd.
pageNoResult page number, 1-based, default 1; page times page_size must not exceed 10000.
sortNoOptional sort order. Allowed values: date_desc (default), date_asc, players_desc.
facetYesrequired,Required facet. Allowed values: app_id, snapshot_date.
app_idNoOptional exact Steam app id filter; pair with sort=date_desc for an app's player-count history.
page_sizeNoPage size, default 20, max 100; page times page_size must not exceed 10000.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

The description adds substantial behavior beyond the readOnly/openWorld annotations: a 50-bucket cap, counts semantics, the fact that page and page_size do not affect counts, that sort is validated but does not change bucket order, and that date scopes snapshot-date counts.

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 front-loaded with the core behavior and each sentence carries useful information about bucket limits, facet values, pagination, sorting, date scoping, or the sibling search tool. There is no filler.

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 full schema description coverage, existing annotations, and an output schema, the description is complete for correct invocation. It covers the critical non-obvious behaviors and points the agent to the sibling tool for daily records.

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 100%, so the baseline is 3, but the description adds meaningful interactions not obvious from the schema: page/page_size do not change counts, sort does not change bucket order, and date scopes snapshot-date counts. It also restates facet values, which is useful but already in the schema.

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 states a specific verb and resource: return facet buckets with counts for one Steam player-count field using search filters. It clearly distinguishes this aggregation tool from the sibling search tool by noting that search is for daily records.

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?

It explicitly points to datasets_steam_playercounts_search as the tool for daily records, implying this tool is for facet aggregation. However, it does not give an explicit when-not-to-use statement or a full decision rule beyond that contrast.

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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