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

With all annotations set to false, the description carries the burden of behavioral disclosure. It adds the key behavior: it returns scored and ranked options with reasoning. It does not mention side effects or auth requirements, but for a decision-support tool this is likely computational; the description provides meaningful context beyond the bare annotation hints.

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 extremely concise: two short sentences. It is front-loaded with 'Decision support' and immediately states the action and output, with no wasted words.

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 relatively simple tool with 4 parameters and no output schema, the description provides the core purpose and return value. It could mention the weighting behavior in more detail, but the essential information for invocation is present.

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 each parameter already has a clear definition. The description reinforces the relationship between options, criteria, and weights but does not add substantive detail beyond the schema. 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 clearly states the tool's function: 'rank options against weighted criteria' and specifies the output ('scored and ranked options with reasoning'). The verb 'rank' plus the resource 'options' is specific and distinguishes it from sibling tools like analyze, reason, and review.

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 use for decision support when you have options and criteria, but it does not explicitly state when to use this tool versus alternatives or provide any exclusion criteria. The context is clear enough but lacks direct comparative guidance.

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