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

With no annotations, the description carries the full burden. It usefully discloses the output shape ('capable/not-capable with specific gaps'), and the operation is evidently a read-only check, so there is little risk to disclose. However it says nothing about permissions, whether missing requirements default to capable, or how partial inputs are treated.

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?

Compact and front-loaded: the triggering questions come first, the return behavior last, with no filler. Slightly example-heavy but every element earns its place.

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?

For a read-only capability check with no output schema, the description states the operation, the triggering scenarios, and the return semantics, which is sufficient to call it correctly. The main residual gap is the undocumented material_id and the interaction between model and requirement fields.

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% and the schema contains a nested 'required' object, so the description must compensate. The examples implicitly map build_size_mm (400×400×400) and layer_thickness_micron (25 micron) and model_id (Bambu X1C), but material_id is never illustrated and no parameter is explicitly named or typed.

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 states a clear function: check whether a given machine can build a part under specified requirements, returning capable/not-capable. Concrete examples (Bambu X1C, 400mm part, 25 micron layer) make the intent unambiguous and implicitly distinguish it from sibling comparison tools like compare_equipment. It stops short of explicitly naming a sibling to defer to.

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?

Three 'use when the user asks...' phrasings give explicit triggering conditions, which is strong when-to-use guidance. There are no when-not conditions or named alternatives, keeping it below a 5.

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