origin_nonlinear_fit_structured

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

With no annotations, the description carries the full burden. It mentions 'explicit function and parameter hints' but does not disclose any behavioral traits such as side effects (e.g., modifying worksheets), authentication requirements, or error handling. This is insufficient for a fitting tool.

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 a single concise sentence, but it sacrifices informative content for brevity. It could be restructured to include key details without significantly increasing 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 the complexity (8 parameters, no schema descriptions, no annotations), the description is grossly incomplete. It fails to explain return values (despite an output schema), parameter relationships, or typical use cases, leaving an AI agent without sufficient 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?

Schema description coverage is 0%, and the description adds no meaning to any of the 8 parameters. The phrase 'explicit function and parameter hints' vaguely hints at the 'function' and 'initial_params' parameters but provides no concrete details about format, constraints, or usage.

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 the tool performs nonlinear fitting with explicit function and parameter hints, distinguishing it from simpler fitting tools like origin_linear_fit. However, it lacks specificity about what 'explicit function and parameter hints' means in practice.

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 provides no guidance on when to use this tool vs. alternatives like origin_linear_fit or origin_run_analysis. No exclusions or context are given.

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