resolve

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

With no annotations, the description transparently explains that the tool evaluates a selector, returns JSON, stores results in session state if a label is given, and describes the ref format. It does not cover error conditions or explicitly state read-only behavior, but the main behaviors are clear.

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 concise yet comprehensive, starting with the core purpose, followed by an example and output details. Every sentence adds value without redundancy.

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?

Given the output schema exists, the description provides sufficient detail about return values and parameter semantics. It could mention any side effects or prerequisites, but overall it is complete for a tool of this complexity.

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 coverage is 0%, so the description must compensate. It explains object_name as 'named object', selector with example and meaning, and label as optional storage. This adds significant context beyond the schema structure.

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 states the tool evaluates a selector expression against a named object and returns a geometry descriptor. It includes examples and details of the return JSON, effectively differentiating it from sibling tools like 'measure' or 'clearance'.

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 explains how to use the tool (selector as Python expression) but does not provide explicit guidance on when to use it versus alternatives, nor does it mention when not to use it or any prerequisites.

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