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

With no annotations, the description carries the disclosure burden. It states that the response contains values only, that polygons must come from another tool, and lists the metrics included. It could add response-size or time-period caveats, but it is transparent about the main behavioral boundary.

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?

Two crisp sentences front-load the core output and keep the polygon caveat in a brief second sentence. No filler or repetition.

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 single-parameter tool with an output schema, the description covers what is returned, the granularity, and the companion geometry source. It is complete enough for an agent to call the tool correctly, though it could add expected format of suburb_name or temporal assumptions.

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 input schema has only a bare suburb_name string with 0% coverage, so the description must carry parameter meaning. The text says 'in the suburb', which conveys that suburb_name selects the target suburb, but it does not specify accepted format/casing or that the name should match a canonical list. This is adequate but not detailed.

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 clearly identifies the deliverable: median advertised weekly house rent per mesh block in the suburb, along with modal street name and dearest/cheapest pockets. It effectively distinguishes itself from suburb-level rent tools by specifying 'every microburb (mesh block)'.

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 'Values only — the matching polygons come from /shapes/mesh-blocks' sentence provides explicit when-not context and points to the companion geometry tool, guiding an agent not to expect polygons here. It does not compare against sibling tools like suburbs_market_median_rent, but the scope of use is clear.

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