matrix_det_3x3

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 states the calculation action but doesn't describe what happens with invalid inputs (e.g., non-numeric strings, wrong matrix dimensions), error handling, performance characteristics, or output format. For a computational tool with zero annotation coverage, this leaves significant gaps in understanding its 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?

The description is a single, efficient sentence that front-loads the core purpose. The domain/category information is concise and adds context without verbosity. However, it could be slightly more structured by separating the calculation statement from the metadata for clarity.

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 tool's computational nature, no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't address input validation, error cases, output format (e.g., numeric result), or mathematical assumptions. For a tool with one parameter but poor schema documentation, more detail is needed to be fully helpful.

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 schema only indicates a 'matrix' parameter as an array of strings without explaining format. The description adds no parameter semantics—it doesn't specify that the matrix should be 3x3, how elements are represented (e.g., as numbers in strings), or ordering (row-major). With low schema coverage and no compensation in the description, this is inadequate.

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 verb ('Calculate') and resource ('determinant of a 3x3 matrix'), making the tool's purpose unambiguous. It also includes domain/category context ('Domain: linear_algebra.matrices, Category: general'), which adds specificity. However, it doesn't explicitly differentiate from sibling tools like 'matrix_det_2x2' or 'matrix_solve_3x3', which would require a 5.

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 doesn't mention when to prefer this over 'matrix_det_2x2' for 2x2 matrices or 'matrix_solve_3x3' for solving systems, nor does it specify prerequisites like matrix format requirements. The domain/category hints at context but lacks explicit usage instructions.

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