probe_material_at

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

With no annotations, the description carries full responsibility for behavioral disclosure. It explains that the tool computes 'the real geometric intersection' rather than using heuristics, and it reveals a common failure mode where an 'open-top enclosure' yields 0 material at the floor. This gives valuable insight into the tool's behavior beyond the basic operation, though it does not explicitly state whether the operation is read-only or has side effects.

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 front-loaded with a one-sentence summary, followed by a rationale with a concrete example, and ends with parameter definitions. No filler; every sentence contributes meaning, making it appropriately sized and well-structured.

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 presence of an output schema, the description does not need to explain return values. It covers the core behavior, parameter constraints, and a key failure scenario, making it complete for a geometric probe tool. It omits error handling, but that is not essential for this use case.

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 descriptions are absent (0% coverage), so the description fully compensates by defining each parameter: doc_name, obj_name, box_min as the minimum corner, and box_size with a positivity constraint. This gives the agent all necessary information to construct valid arguments.

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 opening sentence clearly states the tool's function: 'Check whether solid material actually exists inside an axis-aligned box.' It also distinguishes itself from alternatives by contrasting with 'inferring it from a screenshot or trusting that a cut/pad did what was intended,' providing a specific verb+resource and clear differentiation from siblings like get_view or measure.

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 gives clear usage context: use this tool when you need direct geometric verification rather than visual inference or assumptions from modeling operations. It provides a concrete failure example illustrating when probing is necessary, but it does not explicitly name alternative tools to use instead, so it lacks the most explicit 'use this instead of X' guidance.

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