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

Goes well beyond the annotations with information the annotations cannot convey: a cost model (1 unit per boundary), a hard cap of 50 boundaries, the return shape (GeoJSON Feature with area_km2), and the authentication requirement (API key or connected account). The readOnly/idempotent/non-destructive profile is consistent with a pure geometric computation, so nothing is contradicted.

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?

Four short sentences, each carrying distinct payload: operation definition, use cases, limits and cost, return type and alternative. The core semantic ('union of include minus union of exclude') is front-loaded in the first clause, so an agent skimming the opening already gets the operation right.

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, and the description compensates by naming the return type and its key field (area_km2). For a three-parameter computation tool, limits, cost, auth, and routing to the sibling cover everything needed to invoke it correctly.

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 description lifts it by explaining the set algebra between include and exclude and illustrating it with a worked example, which tells the agent how the two arrays interact rather than just what each holds. The detail parameter's simplification levels are left entirely to the schema, so it stops short of a 5.

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?

Names a specific verb (merges) and resource (boundaries) and then defines the exact set operation: 'the union of include minus the union of exclude,' with a concrete example of three counties minus one city. This clearly separates it from create_area (word descriptions), contains_points, and reverse_boundaries without requiring the schema to be opened.

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?

Gives concrete use cases (sales territories, delivery zones, service areas), names an explicit alternative for the different need ('to describe an area in words instead, use create_area'), and states operational limits (up to 50 boundaries). The agent knows both when to reach for it and where to route elsewhere.

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