matrix_op

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It explains parameter roles but omits return formats, error handling (e.g., singular matrix for inverse), and potential ambiguities like how 'mul' handles two matrices or a matrix and a 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 description is concise and well-organized: When, Params, Example. It front-loads the purpose and uses a compact format that conveys essential information without wasted words.

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 5 parameters and 16 operations, the description covers core usage but lacks detailed behavioral context and edge cases. The presence of an output schema mitigates the need to explain return values, but the single example is not enough to disambiguate all operations.

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?

The schema has zero descriptions, so the description compensates by defining the op values, matrices, vector, n, and angle_mode. It provides an example and clarifies parameter roles, though it leaves some interaction details ambiguous (e.g., vector usage for angle or cross).

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 explicitly states the tool handles matrix/vector algebra and distinguishes it from infix evaluate, which is a sibling tool. The purpose is clear and specific, covering a well-defined domain with a list of 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?

The opening 'When: matrix/vector algebra (not infix evaluate)' provides explicit context for when to choose this tool over the sibling evaluate. It clearly delineates the tool's use case, though it does not name other alternatives.

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