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Get review trend over time

get_review_histogram
Read-only

Analyze Steam game review trends over time with monthly and daily histograms, showing positive and negative counts and percentages to determine if reviews are improving after updates.

Instructions

Get how a game's reviews trend over time by appid: a long-term (monthly) history and the recent per-day breakdown, each with positive/negative counts and positive %. Good for 'are reviews improving / did an update hurt reception'. Get the appid from search_games. No key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appidYesSteam application id (appid). Get it from search_games.
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, indicating safe read with no authentication. The description adds value by detailing the output structure (two time granularities, counts, percentages) and confirming 'No key'. No contradictions.

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?

The description is two concise sentences. The first sentence efficiently states the purpose and output details. The second adds contextual use and parameter sourcing. No redundancy or unnecessary words.

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

Completeness5/5

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

Without an output schema, the description fully explains the return format (two time series with positive/negative counts and percentage). It also provides usage motivation and input source. For a simple one-parameter tool, this is complete.

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% for the single parameter appid, already explaining its purpose and source. The tool description reinforces this by mentioning 'by appid' and 'Get the appid from search_games' but does not add new semantic information beyond what the schema provides.

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 specifies a unique verb-object ('Get how a game's reviews trend over time') and details output components (long-term monthly history, per-day breakdown, counts and percentages). It distinguishes itself from sibling tool get_game_reviews by focusing on aggregated trends rather than individual reviews.

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?

The description provides clear context: it's for assessing review trends over time, specifically 'are reviews improving / did an update hurt reception'. It tells the agent to get the appid from search_games and notes that no key is needed. It does not explicitly exclude use cases but the purpose is well-defined.

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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