run_sensitivity_analysis

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

With no annotations provided, the description carries full burden. It discloses the algorithm (central difference), deterministic nature, optimization (reduces calls), and error handling (returns E500 if time budget exceeded). It does not mention side effects (likely none) or data persistence, but covers key operational traits.

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 exceptionally concise, with three focused sentences. The first sentence states the core function, the second the use case, and the third key behavioral details (error handling, optimization). No wasted 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?

Given the tool's complexity (multiple perturbation parameters, nested laminate input, no output schema), the description omits critical details: the format of the return value (e.g., a table or object) and the structure of the laminate parameter. This forces the agent to guess or risk incorrect 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?

Schema coverage is 0%, so the description must add meaning. It explains that modulus_rel, thickness_rel, and angle_delta_deg are perturbation sizes for each ply, and that laminate is required. However, it does not describe the laminate object structure or what values the defaults represent, leaving significant gaps.

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 it computes sensitivity of D̂11, coupling_ratio, ζ_x to ply-level perturbations in angle, thickness, and modulus. This is specific and distinguishes it from sibling tools like compute_neutral_axis, which focus on different computations.

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 explicitly states the use case (manufacturing tolerance robustness assessment) and notes that the tool reduces repeated agent calls into a single call, implying it should be used instead of multiple iterative calls. However, it does not explicitly contrast with sibling tools beyond the implied domain difference.

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