matrix_determinant

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the core behavior (calculating determinant using SymPy), includes an example with expected output, and specifies the return type ('A key for the determinant expression'). It could improve by mentioning potential errors (e.g., for non-square matrices) or performance considerations, but covers the essential operation well.

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 well-structured and front-loaded with the core purpose, followed by clear sections for Args, Example, and Returns. Each sentence adds value: the first states the action and method, the Args defines the parameter, the Example demonstrates usage with concrete output, and the Returns specifies the result type. 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?

Given 1 parameter with 0% schema coverage and no output schema, the description provides good context: it explains the parameter, shows an example with output, and describes the return value. For a mathematical operation tool, this is largely complete, though it could note dependencies (e.g., requires a square matrix) or link to sibling tools for related 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?

Schema description coverage is 0%, so the description must compensate. It clearly explains that 'matrix_key' is 'The key of the matrix to calculate the determinant for', adding meaning beyond the schema's generic 'Matrix Key' title. The example further illustrates how to obtain and use this key, though it does not detail key format or validation rules.

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 specific action ('calculates the determinant of a matrix') and resource ('matrix'), distinguishing it from sibling tools like matrix_eigenvalues or matrix_inverse. It explicitly mentions using SymPy's det method, providing technical specificity beyond a generic definition.

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 includes an example showing usage after creating a matrix with create_matrix, implying a prerequisite workflow. However, it lacks explicit guidance on when to use this tool versus alternatives like matrix_eigenvalues or matrix_inverse, and does not mention any exclusions or specific contexts for application.

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