heckman

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

Annotations already declare readOnlyHint=true, so the description carries a lower burden. However, it adds little behavioral context beyond the model type; the phrase 'Validation: certified parity evidence' is cryptic and unexplained, and it does not disclose anything about the fitting process, assumptions, or limitations. It does not contradict the annotations.

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 brief (two sentences) and front-loads the primary purpose. However, the second sentence about validation is cryptic and could be omitted or better explained. Overall, it is appropriately sized but not perfectly 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?

For a complex econometric model with 11 parameters and 5 required, the description is extremely sparse. It does not explain the two-step nature, the need for exclusion restrictions, typical use cases, or any caveats. While the schema covers parameter details and an output schema exists, the description provides no high-level context that would help an agent decide to use this tool or understand what the returned object represents. This is inadequate for a tool of this complexity.

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?

The input schema has 100% coverage for all 11 parameters, including detailed descriptions for each. The tool description adds no additional meaning to any parameter, so it stays at the baseline of 3. It does not hurt, but it also does not help.

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 states a specific verb ('Heckman two-step selection model') and a clear purpose ('correcting for sample selection bias'). This clearly differentiates it from most siblings, which focus on other econometric methods. The validation note is odd but doesn't detract from the primary purpose.

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 when to use the tool (when sample selection bias is a concern) but provides no explicit guidance on when not to use it or how it compares to related tools like tobit or truncreg. No alternatives are named, leaving the agent to infer from the purpose alone.

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