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

Beyond the read-only and non-destructive annotations, it discloses important data-quality limitations: marketType is unknown for about 55% of records and transaction_date is missing for about 1.7%. These caveats help an agent interpret aggregates cautiously, though details such as how "top locations" is ranked or limited are not specified.

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 front-loads the recommended use, scope, and sibling alternatives, then lists the returned overview components and key data caveats. Its two dense sentences contain no filler or redundant restatement of the annotations.

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?

For a zero-input aggregate read tool, the description covers scope, selection guidance, alternatives, expected content, and material data limitations. Despite the absence of an output schema, an agent has enough information to choose the tool and set appropriate expectations for its results.

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 tool has no parameters, so there is no parameter behavior requiring explanation. The description appropriately clarifies the fixed whole-database scope instead of inventing filtering options.

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 identifies the resource and scope precisely: an aggregate overview of the entire Polish transaction database, including counts, dates, breakdowns, locations, and price statistics. It explicitly distinguishes this whole-database view from single-place analysis using get_price_statistics or search_transactions.

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?

"Start here" gives a clear entry-point recommendation, while "not one place" states when not to use it. The named sibling tools provide concrete alternatives for place-specific requests.

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