vector_cross_product

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

No annotations exist, so the description carries the full behavioral burden. It does disclose the return shape on success and error plus a worked example, which is meaningful; however, it omits what happens with mismatched dimensions or non-2D/3D inputs and whether a 2D cross product yields a scalar or a 3-vector.

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 docstring structure (purpose, Args, Returns, Examples) is front-loaded and each section earns its place. The example adds concrete value rather than padding, though the Args/Returns scaffolding is slightly verbose for a two-parameter math function.

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?

With no annotations and no output schema, the description covers the essentials (inputs, return shape, error shape, example). It still leaves edge-case behavior – dimension mismatch, 2D result form – undefined, which matters for a function whose valid input space is explicitly restricted to 2D or 3D.

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 the description must compensate, and it does document both parameters as 'a list of numbers.' That is minimal, though – it adds no constraints on element count, matching dimensions between vector_a and vector_b, or numeric type beyond what the schema already says.

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 gives a specific verb ('Computes') and resource ('cross product of two 2D or 3D vectors'), which is unambiguous and distinguishable from siblings like vector_dot_product or vector_magnitude by operation name. It does not explicitly name an alternative sibling, but the operation itself is self-differentiating.

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?

No when-to-use, when-not-to-use, or alternative-selection guidance is offered. The only implicit guidance is the '2D or 3D' dimension constraint, which is really input validation rather than usage routing.

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