serp_measure

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It does not state whether the tool is read-only, whether it operates on existing geometry, what 'targets' means, or what happens if the required parameter is missing. The terse description leaves significant ambiguity for an agent.

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 a single, dense sentence that front-loads the core action ('Measure geometry') and then conveys the parameter dependencies efficiently. Every part earns its place, but the compact format could be slightly improved with clearer separation of the measurement modes.

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?

The tool has three parameters, one required, and no annotations. The output schema exists but is not shown, so the description need not cover return values. However, it fails to explain target references, side effects, error conditions, or how the tool relates to the current scene, leaving it incomplete for nuanced usage.

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 0%, so the description must compensate. It adds the allowed values for 'what' and the dependency between 'what' and the other parameters, which is meaningful. However, it does not explain the coordinate format for 'points' or what 'targets' refer to (object names, IDs, etc.), leaving gaps that the schema does not fill.

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 measures geometry and enumerates specific measurement types (distance, length, area, volume, bbox, centroid). This verb+resource pairing is distinct and establishes a clear purpose separate from sibling tools that create, transform, or select geometry.

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 clear usage context by specifying which parameter is needed for each measurement type ('distance' needs points; others need targets). While it doesn't explicitly exclude alternatives or say 'use this when you need X', the mapping of parameter dependencies gives practical guidance on how to invoke it correctly.

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