matrix_operations

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

With no annotations, the description carries the full burden, yet it only mentions input formatting, not output shapes, constraints (e.g., square matrices for inverse/determinant/eigenvalues), or error behavior. It does not contradict annotations, but it is not transparent about the operation's 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?

Two sentences, front-loaded with the core purpose and immediately followed by an input format example. No 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?

Despite having no output schema, the description does not describe return values or per-operation output differences (e.g., determinant returns a scalar, eigenvalues return a list). For a multi-operation tool with several operations and a required schema, the description leaves significant gaps for an agent trying to interpret results.

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 descriptions cover all three parameters at 100%, and the description's matrix-format example is already present in the schema ('e.g., [[1,2],[3,4]]'). It adds no new parameter-level meaning beyond what the schema provides, so it meets the baseline.

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 specifies 'Perform matrix operations' and lists concrete operations (multiply, inverse, determinant, transpose, eigenvalues), clearly identifying the action and resource. The sibling tools are non-matrix math utilities, so the matrix focus distinguishes it.

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 an input-format guideline ('Matrices should be in array format like [[1,2],[3,4]]'), which is helpful, but it never explicitly states when to prefer this tool over alternatives or when not to use it. The difference from siblings is implied by the matrix-specific language rather than spelled out.

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