rlasso

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

The annotations already declare readOnlyHint=true and openWorldHint=false, covering the safety profile. The description adds one useful behavioral cue: it is a 'faithful port' of hdm::rlasso, implying default behavior and estimation semantics match that R package. However, it does not describe other behavioral aspects such as convergence behavior, runtime, or what exactly the returned object contains.

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, compact sentence with no filler, which is good for conciseness. But it is also sparse for a 14-parameter tool with a large sibling family; it front-loads the port identity yet omits any orientation about what the model does or when to use it. It is not over-written, but it is under-specified.

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 (14 parameters, nested objects, many closely related siblings) the one-line description is not enough. The schema and output schema carry parameter and return-value details, but the description fails to provide context on how this tool fits into the wider lasso workflow or why an agent should invoke it over rlasso_iv, rlassologit, or rlasso_effect.

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 100%, so the schema carries full parameter documentation. The description itself adds no parameter-level meaning; it only names the method. Per the rubric, a baseline of 3 is appropriate when the schema does the heavy lifting.

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 names a specific method and resource: 'Rigorous Lasso / post-Lasso' and ties it to the R package hdm::rlasso. It is not a tautology and clear to a statistically literate agent, but it never states an explicit verb like 'fit' and does not explicitly distinguish itself from sibling tools such as rlasso_iv or rlassologit.

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?

There is no guidance on when to choose rlasso over alternatives. Siblings include closely related estimators (rlasso_iv, rlassologit, rlasso_effect), and the description does not mention when the linear/post-Lasso variant is appropriate or when another tool should be used. Nothing tells the agent about prerequisites, data structure expectations, or fallbacks.

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