matrix_multiply

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. It only states what the tool does ('Multiply two matrices') without any information about constraints (e.g., matrix dimensions must be compatible for multiplication), error handling, performance characteristics, or output format. For a mathematical operation with potential complexity, this is a significant gap.

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 very concise—a single sentence with the core purpose and domain/category context. It's front-loaded with the main action ('Multiply two matrices') and avoids unnecessary words. However, the parenthetical domain/category might be slightly redundant if the context is already clear from the toolset.

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 of matrix multiplication (involving dimension compatibility rules), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't address key contextual aspects like input format details, error conditions, or what the output looks like (e.g., a resulting matrix). For a tool with mathematical precision requirements, this is inadequate.

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 input schema has 2 parameters with 0% description coverage, and the description doesn't add any semantic information about them. It doesn't explain what 'matrix_a' and 'matrix_b' represent, their expected formats (e.g., 2D arrays of numbers), or constraints (e.g., number of columns in matrix_a must equal rows in matrix_b). The description fails to compensate for the lack of schema documentation.

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: 'Multiply two matrices (matrix-matrix multiplication)'. It specifies the verb ('Multiply') and resource ('two matrices'), and the domain/category context helps clarify it's a linear algebra operation. However, it doesn't explicitly distinguish it from sibling tools like 'matrix_add' or 'matrix_scalar_multiply', which would require a more specific differentiation.

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. While the domain/category context ('linear_algebra.matrices') implies the general area, there's no mention of when matrix multiplication is appropriate compared to other matrix operations available in the sibling list (like 'matrix_add', 'matrix_scalar_multiply', 'dot_product', or 'cross_product').

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