matrix_transpose

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'transpose' implies a mathematical transformation, the description doesn't clarify whether this operation is read-only or mutative, what happens with invalid input (e.g., non-rectangular arrays), or any performance considerations. It lacks essential context for safe and effective use.

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 extremely concise—just one sentence plus domain/category annotations. It front-loads the core functionality ('Transpose a matrix') and avoids any redundant or verbose language. Every word earns its place, making it efficient for quick comprehension.

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 complexity (a matrix operation with 1 parameter), lack of annotations, 0% schema coverage, and no output schema, the description is insufficient. It doesn't explain input format, output structure, error handling, or mathematical assumptions (e.g., real numbers only). For a tool with no structured support, more descriptive detail is needed.

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 description adds no parameter information beyond the tool name. The input schema defines a 'matrix' parameter as an array of strings, but the description doesn't explain the expected format (e.g., how rows/columns are represented), constraints, or examples. This leaves critical gaps in understanding how to structure input.

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 clearly states the tool's purpose: 'Transpose a matrix (swap rows and columns)'. It uses a specific verb ('transpose') and resource ('matrix'), making the function unambiguous. However, it doesn't differentiate from sibling tools beyond the domain/category annotation, which is why it doesn't reach a perfect score.

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 provides no guidance on when to use this tool versus alternatives. It includes domain/category annotations ('linear_algebra.matrices, Category: general'), but these are structural metadata rather than usage instructions. There's no mention of prerequisites, limitations, or sibling tools for comparison.

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