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steam_community_recommendations

Fetch a batch of community-recommended Steam store reviews, filtered by review kind, reviewer playtime, language, and region, returning author, playtime, votes, and app details.

Instructions

Get the store's community-recommended reviews feed. Returns a batch of recent, quality user reviews recommended across the whole store (author, playtime, helpful votes, and the recommended app). Filter by review kind/sort, reviewer playtime window, review language, and store region. The endpoint serves a fixed batch and does not support tag filtering or deep pagination.

Input Schema

NameRequiredDescriptionDefault
lNoLanguage code
ccNoStore country code (ISO, selects currency)
playtime_maxNoMaximum reviewer playtime in hours (0 = no maximum)
playtime_minNoMinimum reviewer playtime in hours (0 = no minimum)
review_filterNoReview kind / sort
review_languageNoReview language: 'my_languages' or a Steam language name

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / review_filter / enum
      Added value: +[
+  "helpful",
+  "recent",
+  "funny"
+]
  2. Addedv1.5.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses the payload shape (author, playtime, helpful votes, recommended app) and important limitations (fixed batch, no tag filtering, no deep pagination). It still omits safety/rate or caching behavior, but the pagination and fixed-batch disclosure is real added value.

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?

Three sentences, front-loaded with purpose, then the return fields, then constraints. Nothing is redundant, though the parenthetical field list is the only slightly expendable portion.

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?

For a 6-parameter, no-output-schema read feed, the description covers what it returns and its key limits (fixed batch, no pagination). It could say more about the batch size or read-only nature, but an agent has enough to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter is already documented. The description loosely maps parameter groups ('review kind/sort, reviewer playtime window, review language, and store region') but adds no format or value details beyond the schema, so the baseline 3 is appropriate.

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 specifies a concrete verb ('Get') and a concrete resource ('the store's community-recommended reviews feed'), and it even enumerates the returned fields. The 'across the whole store' phrasing quietly distinguishes it from per-app review tools, but it never names a sibling such as steam_reviews, so the differentiation is only implicit.

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?

Usage is implied by 'store's community-recommended reviews feed', and the closing sentence gives useful negative constraints (no tag filtering, no deep pagination). However, it offers no explicit when-to-use guidance or named alternative for retrieving reviews of a specific app, leaving that choice to inference.

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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