trajectory_sensitivity_analysis

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

With no annotations, the description carries the full burden. It discloses that errors are returned as formatted strings (no exceptions raised), which is key behavioral info. However, it does not explicitly state the tool is read-only or safe for repeated calls, but the nature of analysis implies no side effects. The error handling disclosure is valuable.

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 moderately concise and well-structured with 'Args', 'Returns', and 'Raises' sections. It avoids fluff and adds value through structured documentation, though the docstring format slightly increases length. Overall, efficient.

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 (3 parameters, nested objects, no annotations) and rich sibling set, the description covers basic purpose and return format but omits input structure details. An output schema exists but is not described. The description is adequate for simple use but lacks depth for correct 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 description coverage is 0%, requiring the description to compensate. The description provides minimal one-line comments for each parameter (e.g., 'Baseline rocket geometry,' 'Parameters to vary and their ranges'), but lacks details on expected structure, required keys, or formats. For complex objects like 'rocket_geometry', this is insufficient.

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 'Perform sensitivity analysis on rocket trajectory parameters,' using a specific verb and resource. It distinguishes from siblings like 'rocket_3dof_trajectory' (which runs a trajectory) and 'monte_carlo_uncertainty_analysis' (probabilistic), making the purpose unambiguous.

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 implies use for understanding parameter impact on trajectory, but provides no explicit guidance on when to use this tool versus alternatives like 'monte_carlo_uncertainty_analysis' or 'optimize_launch_angle'. No when-not-to-use or exclusion criteria are given.

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