Skip to main content
Glama

Crawlora MCP

datasets_steam_reviews_search

Read-only

Search the Steam reviews dataset (most-helpful reviews per game).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoOptional full-text query over the review body, max 256 characters.
pageNoResult page number, 1-based, default 1; page times page_size must not exceed 10000.
sortNoOptional sort order. Allowed values: votes_desc (most-helpful first, default), weighted_desc, date_desc.
app_idNoOptional exact Steam app id filter.
languageNoOptional review language filter (e.g. english, schinese).
voted_upNoOptional recommendation filter: true (positive) or false (negative).
page_sizeNoPage size, default 20, max 100; page times page_size must not exceed 10000.

Output Schema

TableJSON 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. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only the scope note that results are most-helpful reviews per game; pagination limits and result format are handled elsewhere, so it adds modest value beyond the annotations.

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?

A single front-loaded sentence with zero filler; the resource and scope qualifier come first, which is exactly what an agent needs to triage.

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?

With an output schema, full parameter coverage and annotations present, the description is functionally adequate. However, for a dataset tool that sits beside several similarly named Steam review tools, it omits any routing guidance, leaving a real gap.

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 description coverage is 100% and each of the 7 parameters is documented in the schema with format, defaults and constraints. The description adds no parameter meaning beyond that, 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?

States a specific verb (Search) and resource (Steam reviews dataset), with a parenthetical that scopes it to most-helpful reviews per game. An agent can tell it apart from datasets_steam_games_search or datasets_steam_news_search by resource, though it doesn't explicitly name any sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no when-to-use or when-not guidance and names no alternatives. It implies a full-text search use case but leaves the agent to infer how it differs from the non-dataset steam_reviews and steam_reviews_histogram tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources