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datasets_steam_prices_search

Search the Steam prices dataset for daily game price time series. Filter by app ID or date to get price history or snapshots.

Instructions

Search the steam-prices dataset. Searches the daily price time series for priced games (one document per appid × day; integer cents). Pair app_id with sort=date_desc for a game's price history, or pass date for one day's snapshot. Sort enum: date_desc (default), date_asc, price_asc, price_desc, discount_desc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoSnapshot date filter yyyy-MM-dd
pageNoPage number, defaults to 1
sortNoSort enum: date_desc, date_asc, price_asc, price_desc, discount_desc
app_idNoExact Steam app id filter
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. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "date_desc",
+  "date_asc",
+  "price_asc",
+  "price_desc",
+  "discount_desc"
+]
  2. Added
  3. Removedv1.6.0
  4. Addedv1.5.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations to lean on, the description discloses key behaviors: one document per appid×day, integer cents, priced games only, and the sort options including the default. It does not describe response shape, but for a read-only search tool this is a solid disclosure of behavior beyond what the schema states.

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 compact and front-loaded, with the dataset scope and granularity stated first. It avoids fluff, though the opening sentence and second sentence are slightly redundant and the sort enum is repeated from the schema.

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?

Given no output schema and no annotations, the description covers the essential semantics the agent needs: dataset granularity, currency unit, filtering patterns, and sort behavior. It does not spell out the returned fields, but the sortable dimensions (price, discount, date) are inferable from the description.

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 extra meaning: it explains how `app_id` and `sort` combine for a price history, that `date` yields a snapshot, and that `date_desc` is the default. This goes beyond the schema's one-line parameter descriptions.

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 names a specific verb and resource ('Search the steam-prices dataset') and characterizes the data shape precisely: 'daily price time series for priced games (one document per appid × day; integer cents)'. This clearly distinguishes it from sibling steam dataset searches like datasets_steam_news_search or datasets_steam_achievements_search.

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 gives explicit recipes: pair `app_id` with `sort=date_desc` for a game's price history, or pass `date` for a single-day snapshot. It does not name alternative tools or state when not to use this one, but the usage patterns are concrete enough for an agent to proceed correctly.

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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