estimate_and_diagnose

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

With no annotations, the description discloses the estimation method (MVENC maximum likelihood), the exact diagnostic tests run, and the side effects of output_path (writes .pre and .out files, default is screen-only). This goes beyond basic safety but does not mention error handling or prerequisites.

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 structured with a leading action sentence, a behavior paragraph, and a clear parameter list. Every sentence adds value, and it is not overly long.

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?

The tool has moderate complexity, no annotations, no output schema, and a sparse schema. While input and side effects are well explained, the return value is never stated—it is unclear whether the function returns diagnostic results, the fitted model, or nothing. This is a key gap.

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 schema having no descriptions, the description explains inp_path as the model specification file and output_path in detail (persist .pre/.out, default behavior). Both parameters are fully covered with context beyond their names.

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 fits a model from an .inp file and runs a full diagnosis, listing specific tests (standardised residuals, ACF/PACF, Ljung-Box, Jarque-Bera, seasonality). This distinguishes it from sibling tools by combining estimation and diagnosis in one step.

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 does not explicitly state when to use this tool versus alternatives like confirm_and_estimate. It implies this is a 'clean path' and mentions that output_path mirrors confirm_and_estimate's file trio, but gives no direct guidance or exclusions.

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