laplacian

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

No annotations are provided, so the description carries the full burden. Defining the result as 'the sum of second derivatives' is genuinely useful behavioral context about what is computed, but there is no mention of the coordinate system assumed, whether the result is symbolic, or error behavior for non-scalar input.

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?

A single front-loaded sentence with no filler; the operative verb and resource come first and the clarifying definition follows.

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?

For a two-parameter symbolic computation tool with no annotations, no output schema, and no parameter documentation, the description is too thin. It omits what 'variables' controls and what form the returned expression takes.

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% and the description only indirectly covers 'expr' via 'scalar expression'. It says nothing about the 'variables' parameter, which determines which variables the derivatives are taken with respect to, leaving half the parameter set undocumented in both schema and prose.

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?

States a specific verb (Compute) and resource (the Laplacian of a scalar expression), and even clarifies the mathematical definition. However, it does not differentiate itself from close siblings like gradient, divergence, or curl, which an agent operating in this calculus family would need.

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?

There is no guidance on when to use this versus gradient/divergence/curl/symbolic_calculus, nor any prerequisites or exclusions. The agent must infer applicability from the definition alone.

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