step_by_step_laplace

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

With no annotations provided, the description carries the full burden. It clearly discloses that the tool returns both derivation steps and the final answer, and it lists the transformation properties it shows. This is substantive behavioral information, though it does not mention limits or special cases.

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 two sentences, front-loads the core action, and then efficiently adds the step-by-step behavior, properties covered, and return value. No unnecessary words.

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 is adequate for a simple one-parameter math tool and the output schema covers return values, but it omits input format details and does not explicitly contrast with laplace_transform_signal, so an agent has to infer some usage context.

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 schema has only one parameter, 'expression', with 0% schema description coverage. The description adds meaning by identifying it as f(t), the function to transform, but does not explain expected syntax, variable conventions, or whether LaTeX/plain math input is used.

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 uses a specific verb ('Solves'), names the exact resource ('Laplace transform of f(t)'), and clarifies the step-by-step nature. It further distinguishes the tool from the sibling laplace_transform_signal by emphasizing derivation steps rather than a direct result.

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 step-by-step phrasing implies this tool is for cases where a derivation is wanted, but there is no explicit statement about when not to use it or which sibling alternative is appropriate for just obtaining the transform. Context is implied, not stated.

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