evaluate_tradeoffs

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

With no annotations provided, the description fully carries the behavioral disclosure burden. It reveals the EU calculation, ranking behavior, and the INDETERMINATE return (recommended=null) when the top-2 scores differ by <0.05, as well as the purpose of context for escalation/stall detection. This is thorough for a pure computation 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 front-loaded with the core function, then provides an exact input template, validation rules, and edge-case behavior. The JSON example is lengthy but earns its place as a 'copy this structure exactly' requirement. No filler content is present.

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 a complex nested schema and no output schema, so the description must compensate. It explains the key return behavior (indeterminate with null recommendation), but does not fully specify the output structure (e.g., what fields are returned for ranked options). The context parameter's effect on escalation/stall detection is mentioned but not detailed.

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 coverage is 100% and includes descriptions for all parameters, so the baseline is 3. The description adds a concrete JSON example and clarifies the probability tolerance (+/-0.01) and minimum options, enhancing practical understanding beyond the schema alone.

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 opens with 'Compare options by computing Expected Utility (EU) for each, then rank them,' which clearly states the tool's verb (compare), resource (options), and method (EU, ranking). It distinguishes this tool from sibling validation/checking tools by focusing on tradeoff evaluation rather than confidence or reasoning validation.

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 specifies the required input structure and validation constraints (probabilities sum to 1.0 ±0.01, minimum 2 options) and explains when to use the optional context parameter for escalation/stall detection. However, it does not explicitly mention alternatives or when-not-to-use scenarios, so it lacks exclusion guidance.

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