athena_dro_resource_select

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says the tool 'selects' a subset and enumerates exactly below a threshold, but it does not disclose side effects, output format, error behavior, or what happens when the threshold is exceeded. This is too thin for a complex selection tool.

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 dense sentence with the core action front-loaded and no filler. Every phrase contributes essential information about the mathematical model and the enumeration limit, making it highly concise and 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?

This is a high-complexity tool with 6 parameters, nested objects, and no output schema, yet the description is only one sentence. It omits return values, parameter formats, exact behavior above the threshold, and any prerequisites or failure modes. An agent lacks critical information needed to invoke it correctly.

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 0%, so the description must compensate. It maps a few concepts to parameters (covariances, ambiguity_radius, exact_limit), but it does not explain required params like candidates, budgets, and covariances, nor the optional alpha parameter. The domain jargon gives hints but not enough semantic grounding for an agent to construct valid arguments.

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 uses a specific action ('Select a finite candidate subset') and names the exact problem setting ('correlated Gaussian resource covariance plus ellipsoidal mean ambiguity'), which clearly distinguishes it from sibling tools like athena_chance_resource_select and athena_two_stage_resource_plan. It also states a scope condition ('exact enumeration only below the declared threshold'), making the purpose unmistakable.

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 conveys the appropriate context for use: DRO resource selection with Gaussian covariance and ellipsoidal ambiguity, plus a limiting condition about exact enumeration. However, it does not explicitly state when to prefer this tool over alternatives, nor what to do when the threshold is exceeded. Thus it provides clear context but no exclusionary guidance.

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