matrix_operation

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 does not state whether the operation is read-only, what side effects may occur, or what the return value looks like. It only gives examples of operations, leaving the agent uninformed about important behavioral aspects.

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 wasted words. It front-loads the action. It could include more detail without becoming verbose, but its brevity is not a flaw.

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?

The tool is simple with a full schema and output schema, so the description does not need to explain returns. However, it lacks behavioral context and usage guidance, making it only minimally viable. It is adequate for a basic understanding but incomplete for confident selection and invocation.

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% parameter coverage with clear descriptions for 'matrix' and 'operation'. The description merely lists examples that are already enumerated in the schema, adding no new semantic meaning beyond what the schema provides.

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 that the tool performs a matrix operation, with examples (det, inverse, eigenvalues). This distinguishes it from non-matrix tools like solve_ode or calculate_expression. However, it does not explicitly differentiate from the sibling tool matrix_multiply, leaving slight ambiguity about whether matrix multiplication is included.

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 does not mention matrix_multiply for multiplication or any exclusions. The agent must infer usage from the tool name and examples alone.

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