origin_linear_fit

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

No annotations are provided. The description only says 'run' without disclosing side effects (e.g., does it modify the worksheet? create a new output sheet?), the nature of the fitting (e.g., least squares?), or any limitations. The agent cannot infer what happens beyond the tool's name.

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 extremely terse (3 words), which is concise but not informative. It lacks structure and fails to provide enough context for effective tool selection. It is under-specified rather than efficiently concise.

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 (7 parameters, no parameter descriptions, no annotations, and an output schema not described), the description is grossly incomplete. It does not cover return values, parameter usage, or operational details, leaving the agent without sufficient information.

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?

With 0% schema description coverage, the description must compensate but adds nothing about the seven parameters (worksheet, x_col, y_col, output_sheet, options, include_output, output_max_rows). The agent has no help understanding what these parameters mean or how to use them.

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 'Run Origin linear fitting' clearly states the action (run) and resource (linear fitting). It distinguishes from sibling tools like polynomial_fit and nonlinear_fit by specifying linear fitting, though it could be more explicit about what linear fitting entails (e.g., fitting a straight line to data).

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 versus alternatives (e.g., polynomial_fit, nonlinear_fit). There is no mention of prerequisites, data requirements, or context for selecting linear fitting over other fitting methods.

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