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by net.crawlora
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datasets_steam_achievements_facets

Read-only

Return up to 50 app-id facet buckets with counts for the Steam achievements dataset, honoring the app_id filter from datasets_steam_achievements_search. facet accepts only app_id; page and page_size do not change counts; sort is validated but does not change bucket order. Use datasets_steam_achievements_search to find achievement 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_achievements_facets"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoResult page number, 1-based, default 1; page times page_size must not exceed 10000.
sortNoOptional sort order. Allowed values: percent_desc (most-unlocked first, default), percent_asc (rarest first), rank_asc.
facetYesrequired,Required facet. Allowed values: app_id.
app_idNoOptional exact Steam app id filter; pass an app id to list its achievements.
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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds real behavioral detail beyond that: a cap of 50 buckets, that page/page_size do not affect counts, and that sort is validated but does not reorder buckets — all non-obvious traits worth knowing.

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?

Four short sentences, front-loaded with the return shape and count cap, then constraints, then the alternative routing. Dense and largely waste-free, though the constraint list could be compressed slightly.

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?

An output schema exists, so return values needn't be spelled out, and the description still characterizes the response (buckets with counts, up to 50). Combined with the pagination/sort no-op notes and the sibling pointer, an agent has what it needs; only modest room remains.

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 earns above that by explaining effects the schema does not: facet accepts only app_id, pagination does not change counts, and sort changes nothing about bucket order. These are meaningful semantic clarifications for parameters the schema merely enumerates.

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?

States a specific verb and resource ('Return up to 50 app-id facet buckets with counts for the Steam achievements dataset') and immediately scopes it against the sibling search tool. An agent can distinguish this facet-count tool from datasets_steam_achievements_search without opening either schema.

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?

Names the alternative explicitly ('Use datasets_steam_achievements_search to find achievement records') and clarifies that facet only supports app_id, which signals the intended use. It stops short of an explicit when-to-use/when-not statement for facet counting itself, so routing is clear but not exhaustive.

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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