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JavaScript
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datasets_steam_charts_search

Search daily snapshots of Steam's player-count and sales charts to retrieve current rankings, player numbers, or an app's historical rank and player trends across countries.

Instructions

Search the steam-charts dataset. Searches daily snapshots of Steam's player-count and sales charts, stored in a search index (one document per chart × country × snapshot × rank) so history accumulates. Charts: most_played (weekly peak concurrent), concurrent (live concurrent players), top_sellers (weekly sales; country-specific). With no date the latest snapshot is returned (today's chart); pair app_id with sort=date_desc for an app's rank/players over time. Country is global for the player-count charts or an ISO code (e.g. us) for top_sellers. Sort enum: rank, rank_desc, date_desc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over the game name, max 256 characters
dateNoSnapshot date filter yyyy-MM-dd; defaults to the latest snapshot
pageNoPage number, defaults to 1
sortNoSort enum: rank, rank_desc, date_desc
chartNoChart enum: most_played, concurrent, top_sellers
app_idNoExact Steam app id filter; pair with sort=date_desc for rank/players history
countryNoMarket filter: global (player-count charts) or an ISO country code (top_sellers), max 128 characters
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / chart / enum
      Added value: +[
+  "most_played",
+  "concurrent",
+  "top_sellers"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "rank",
+  "rank_desc",
+  "date_desc"
+]
  2. Added
  3. Removedv1.6.0
  4. Addedv1.5.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does describe the underlying data model (one document per chart × country × snapshot × rank) and hints at historical accumulation, but it does not explicitly state that the operation is read-only or disclose pagination constraints (e.g., page*page_size limit) beyond what's in the schema. It gives context on behavior but not a full safety profile.

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?

The description is moderately concise, about five sentences, and logically organized: opening with the purpose, then the data model, chart specifics, usage tips, and a final note on sort enum. It is front-loaded with the key action. However, it redundantly reiterates the sort enum values that are already fully listed in the schema, adding minor bloat.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, the description should describe what the tool returns. It only implicitly explains the document structure (chart × country × snapshot × rank) but does not state the fields present in results (e.g., rank, players, revenue). It also does not mention pagination behavior or result limits beyond the schema's page_size description. For a search tool with this complexity, the absence of explicit output description leaves a gap.

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%, but the description adds significant meaning: it explains what each chart type measures (most_played weekly peak concurrent, concurrent live players, top_sellers country-specific weekly sales), clarifies the default date behavior, and instructs on pairing app_id with sort for history. This exceeds the schema descriptions and helps an agent select and construct queries correctly.

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 clearly states the tool searches the steam-charts dataset, and elaborates on what that dataset contains (daily snapshots of player-count and sales charts) and the specific chart types. This distinguishes it from siblings like 'steam_charts_concurrent' or 'datasets_steam_playercounts_search' by framing it as a historical index search. The verb+resource is specific and unambiguous.

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?

Provides clear practical usage guidance: with no date the latest snapshot is returned, pairing app_id with sort=date_desc gives history, and it explains country semantics for different charts. However, it does not explicitly mention alternative tools or state when not to use this tool versus a direct chart endpoint, so it stops short of full exclusions.

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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