calculate_stability_derivatives

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

The description discloses error handling (returns formatted strings, no exceptions), output structure (JSON string with derivative definitions), and the nature of the calculation. With no annotations, it provides sufficient behavioral context, though it omits potential limitations or side effects.

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 well-organized with Args, Returns, Raises sections and is front-loaded with purpose. While slightly verbose in repeating derivative definitions, it remains clear and structured, earning its length.

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 no annotations, the description covers inputs, outputs, and error behavior adequately. It explains nested object structures and includes defaults, though it could mention more about the derivation method or assumptions. Overall, it equips the agent to use the tool correctly.

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?

Despite 0% schema description coverage, the description extensively details each parameter with keys, types, defaults, and optional fields (e.g., 'span_m: Wing span in meters', 'alpha_deg: Reference angle of attack (optional, default 2.0)'). This compensates fully for the sparse 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 states it calculates basic longitudinal stability derivatives for a wing, specifying the scope and output. However, it does not explicitly distinguish from sibling tools like wing_vlm_analysis, but the purpose is still specific and actionable.

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 lacks guidance on when to use this tool versus alternatives. It does not mention prerequisites, ideal scenarios, or when other tools might be more appropriate, leaving the agent without decision support.

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