mateigen

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

No annotations are present, so the description bears full responsibility. It does not mention output format, handling of non-square matrices (though schema requires square), numerical stability, or whether eigenvalues are returned as real/complex. This is insufficient for a numerical tool.

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 concise sentence with no filler. It is front-loaded and efficient, though it could be slightly more structured (e.g., mentioning that the matrix must be square as stated in the schema).

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 eigenvalue computation and the presence of an output schema (not detailed), the description is too minimal. It fails to disclose return value type, required matrix property (square is in schema but not description), or precision implications.

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 100% coverage for the single parameter 'm' with description 'Square matrix.' The description adds no extra meaning beyond the schema, resulting in baseline score of 3.

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 computes eigenvalues of a matrix, using a specific verb and resource. It distinguishes itself from sibling matrix tools like matdet and matinv, though it could mention that it returns eigenvalues only (not eigenvectors).

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?

No guidance is provided on when to use this tool versus alternatives like hess for Hessian matrices or matdet for determinants. The context signals show many sibling tools, but the description offers no when/when-not advice.

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