cross_sections

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

No annotations are provided, but the description details the return format (list of {position, area} pairs), parameter defaults (axis default Z, num_slices default 10 with min 2), and object_name default. It lacks disclosure of edge cases (invalid object, axis) but overall is sufficient for expected behavior.

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?

Every sentence adds value. The core function, output format, parameter details, and use cases are presented efficiently with no redundancy. Front-loaded with the main action.

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 description covers all parameters, output format, and use cases. Output schema exists but is not provided, yet the description sufficiently describes return structure. Minor gaps (error handling) but adequate for a simple 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 coverage is 0%, so description compensates by explaining axis options (X, Y, Z), num_slices constraints, and object_name usage. Adds context beyond schema defaults and titles, though could clarify axis is a string enum.

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?

Clearly states the tool computes cross-sectional areas at evenly spaced planes along an axis. It specifies the verb 'Compute' and resource 'cross-sections', and distinguishes from sibling tools like 'measure' or 'shape_compare' which serve different purposes.

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 use cases such as detecting internal voids or verifying cross-section profiles, but does not explicitly state when not to use or compare to alternatives like 'clearance' or 'interference'. The guidance is implied rather than explicit.

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