Analyze thousands of Steam reviews to reveal sentiment over time, by language, playtime, Deck, purchase type, and developer replies.
Analyze thousands of a game's reviews: sentiment over time, by language, playtime, Deck, key vs Steam purchase, dev replies.
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Changes observed during successful MCP inspections.
v1.18.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes that this is a safe read operation, so the description does not need to repeat that. It adds useful scope ('thousands', 'sentiment over time') but does not disclose operational details like pagination via cursor, request-volume implications, or output format behavior beyond what the schema already captures.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single tight sentence with a front-loaded verb/resource and a colon-separated capability list. There is no filler, redundancy, or unnecessary background.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested parameter object with nine settings, no output schema, and a fairly complex analytical behavior. The one-line description does not explain return value shape, cursor-based pagination, output format selection, or performance/request trade-offs, leaving an agent without sufficient context for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description hints at dimensions that map to parameters ('by language' → language, 'key vs Steam purchase' → purchase_type), but it provides no parameter-level guidance, defaults, constraints, or trade-offs. Given schema_description_coverage is 0% for the top-level tool signature, the description fails to compensate for undocumented parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource — 'Analyze ... a game's reviews' — and enumerates concrete analytical dimensions (sentiment over time, language, playtime, Deck, purchase type, dev replies). It clearly signals an aggregation/analysis tool rather than a raw review fetcher like steam_get_app_reviews, though it does not explicitly name any sibling alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool vs alternatives such as steam_get_app_reviews or steam_analyze_game. The word 'Analyze' implies the use case, but no exclusions, prerequisites, or contrasting sibling conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.