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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is well covered. The description adds useful behavioral context: results come from joined public records, and the tool returns a true matching row count, up to six example rows, and a link to the complete file. This goes beyond the annotations without contradicting them.

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 front-loaded with the core action and immediately communicates the two usage modes and the output contract. The em-dash list of query types is dense but informative, and the three example invocations all earn their place. It is slightly long, but no sentence feels wasted.

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 tool with 5 parameters, full schema coverage, rich annotations, and an output schema, the description covers the essential invocation modes (property-level vs market-level), the output shape, and the domain of records. Nothing an agent needs to call this tool correctly is missing.

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 the baseline is 3; the schema already thoroughly documents `address`, `within_ft`, `columns`, `scope`, and `dataset`. The description reinforces the address omission rule and provides examples, but it does not add meaning materially beyond what the input schema already provides. A 3 is appropriate given the schema carries the 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 names a specific action ('Answers a question') and a concrete resource: joined public records for the Minneapolis-St. Paul metro, with an enumerated range of query types such as sales, ownership, contamination, licensing, and census comparison. The address-or-market distinction and concrete example invocations make the tool's purpose unambiguous. It does not explicitly name a sibling tool, but the question-answering role is clearly distinct from the analysis/scoping siblings.

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?

The description explicitly states the main usage branch: give an `address` to answer about one property and its surroundings, omit it to ask about the whole market. The example invocations illustrate realistic query shapes. It does not spell out when to prefer sibling tools, but the dependency on twin_cities_datasets is visible in the schema and the market-vs-property guidance gives clear conditions.

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