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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds the useful fact that the dataset is a daily price/discount time series, which tells the agent what kind of records to expect, but says nothing about pagination limits (beyond the schema), result shape, or freshness.

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?

One front-loaded sentence with no filler; the resource and its content are stated immediately. It is efficient, though extremely terse for a search tool.

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?

An output schema exists and annotations cover the safety profile, so the description needn't explain returns or read-only behavior. What remains – a brief cue that this is a time-series price/discount dataset – is present and sufficient for an agent to call it correctly.

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?

Schema description coverage is 100%, so all five parameters (date, page, page_size, sort, app_id) are already documented in the schema. The description adds no additional parameter meaning, so the baseline of 3 applies.

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?

States a clear verb ('Search') and a specific resource ('the Steam prices dataset'), then clarifies the dataset's content as daily price and discount time series. This distinguishes it from adjacent siblings such as datasets_steam_games_search, datasets_steam_charts_search and datasets_steam_playercounts_search, though it doesn't name them explicitly.

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 guidance about when to choose this tool over the many other Steam dataset tools, nor any prerequisites or exclusions. Usage is only implied by the word 'Search'.

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