cate_summary

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is known. The description only restates the core purpose and adds no additional behavioral context—it does not mention that as_handle caches results on the server, that result_id allows reuse of a previous fit, or that data loading may occur via data_path. With annotations taking care of side effects, the description fails to disclose these operational behaviors.

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, front-loaded sentence with no filler—every word earns its place. It is crisp and efficient, though perhaps too terse for a tool with seven parameters magazine; it is appropriately sized for a concise purpose statement but could benefit from expansion. A 4 reflects solid concision without perfection.

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?

Despite an output schema and 7 parameters, the description gives no overview of how cate_summary fits into a causal inference workflow. It does not mention that result comes from metalearner(), that as_handle enables chaining, or how it differs from sibling summary tools like rd_cate_summary. The agent is left to infer the tool's role and usage from parameter descriptions alone, which is insufficient given the tool's 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?

Schema description coverage is 100%, so all seven parameters are individually documented. The main description adds nothing about parameters—it does not explain the relationship between result and data_path, nor the purpose of detail levels. The schema carries the burden, so baseline 3 is appropriate.

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 'Descriptive statistics of the CATE distribution' uses a clear noun phrase that identifies the tool as a summarizer of CATE distributions without an imperative verb. It is unambiguous about the core function but does not explicitly differentiate from similar siblings like rd_cate_summary or cate_eval, so it loses a point.

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?

No guidance is provided on when to choose this tool over alternatives such as rd_cate_summary, cate_eval, or focal_cate. It does not mention prerequisites (e.g., that result must come from metalearner()) or whether it can operate on raw data via data_path. The only usage-related hint lies in the detail parameter description, which addresses payload depth rather than tool selection.

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