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

With no annotations, the description carries the full burden and discloses key behavioral traits: similarity is statistical, not geographic, and results are typically spread across the country. However, it does not describe the output format, ordering, or how the statistical profile is computed, leaving some uncertainty about what the agent will receive.

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 two sentences long, front-loaded with the core purpose, and every sentence earns its place. The first sentence defines the action and scope; the second adds a usage example and a key behavioral caveat. No wasted words.

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?

There is no output schema, so the description should explain what the return value looks like. It states the results are postal areas similar to the given one, but does not mention whether they include similarity scores, how many results are returned (though the limit parameter implies this), or how the list is ordered. For a moderately simple tool this is a noticeable gap but not crippling.

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 schema already fully documents all three parameters. The description adds no parameter-specific details beyond the schema; it only implies the 'place' parameter contextually. The baseline of 3 is appropriate since the schema does the heavy lifting.

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 uses a specific verb ('find') and resource ('statistical profile') while clearly distinguishing from siblings by emphasizing the whole statistical profile across income, age, education, housing, and employment, not just one metric. It also differentiates from geographic similarity, which helps separate it from tools like compare_areas or get_area_stats.

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 provides a concrete use case ('where else in Finland feels like this neighbourhood?') that implies when to use the tool. It does not explicitly mention alternatives or exclusions, but the framing is clear and sufficient for an agent to decide.

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