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

Annotations already declare it read-only, non-destructive, and closed-world, so the safety burden is lifted. The description adds genuinely useful behavioral context by spelling out the return shape (target code, signals used, ranked peers) and the distance semantics (0 identical, 1 maximally distant) plus the per-comparison signal count.

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?

Three sentences, front-loaded with the core action, then output semantics, then the sibling routing. Every clause carries information; nothing is padding.

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?

Despite no output schema, the description fully explains what is returned and how to interpret distances and signal counts. Combined with annotations and full param coverage, an agent has everything needed to call and interpret it.

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 both parameters (area formats, k default/min/max) are already fully documented in the schema. The description adds only the geographic constraint, which the schema also states, so the baseline 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 specific verb (Finds), resource (neighbourhoods most similar to one place), geographic scope, and the method (nearest-neighbour distance over normalised signal values). It explicitly names the sibling find_areas as the different case, so an agent can separate the two without opening schemas.

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?

Directly tells the agent when to use it ('areas like this one') and when to prefer the alternative ('for a ranking filtered by named signals, find_areas'). No inference required.

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