vector_calculus_operation

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

With no annotations, the description carries the full burden of behavioral disclosure. It provides no information about side effects, return formats, error handling, or workspace behavior. It only restates the operations already present in the schema, adding no behavioral insight.

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, focused sentence with no filler. It is concise and front-loaded, though it could be slightly more structured by noting that gradient/laplacian take scalar fields while divergence/curl take vector fields. Its brevity is a strength.

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 description provides almost no value beyond the operation list, even though the tool has four parameters and an output schema. It fails to explain the scalar/vector distinction, session usage, or relationship to sibling tools. The schema compensates partially, but the standalone description is incomplete.

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 100%, so the baseline is 3. The description lists the operations, which duplicates the operation parameter's explanation, and adds nothing about the expression format, variables, or session behavior. It neither improves nor degrades parameter understanding beyond the schema.

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 identifies the tool as performing vector calculus operations and enumerates the specific operations (gradient, divergence, curl, laplacian). This distinguishes it from scalar calculus tools like differentiate_expression, though it lacks an explicit verb like 'compute'.

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 such as differentiate_expression or integrate_expression. The operation list gives implicit context, but there is no explicit mention of when to use or avoid this tool.

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