measure

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

No annotations provided, so description carries full burden. It explains that queries are fast (e.g., topology is fastest for boolean confirmation) and that summary returns multiple values. However, it does not discuss error handling, bounds, or data precision, though these are less critical for a query tool.

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?

Single paragraph, front-loaded with main purpose. Every sentence adds value, but could be more structured (e.g., bullet points for query types). Not overly verbose.

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?

Covers main use cases, references sibling tools, explains complex parameter interaction (clearance). Output schema likely covers return values, so description does not need to repeat them. Overall adequate for a query tool.

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%, but the description adds meaning: query lists possible values (though not as enum), object_name/object_name2 are named objects from show(), and clearance requires both. This significantly enriches the bare schema.

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 queries geometry of a shape, lists specific query types (bounding_box, volume, area, etc.), and distinguishes itself from render_view by emphasizing numerical unambiguity. It also explains the purpose of specific queries like topology for boolean operations.

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?

Provides explicit guidance: prefer measure over render_view when verifying geometry, use summary to orient quickly, use topology to confirm boolean success, and notes that clearance requires both object_name and object_name2. This helps the agent decide when to use this tool versus alternatives.

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