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

With no annotations, the description carries full responsibility for disclosing behavior. It only mentions asking calibrated humans; it does not disclose cost implications, asynchronous behavior, task creation, data handling, or what happens after the comparison is requested.

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 short and free of fluff, but it is so underspecified that the conciseness comes at the expense of clarity. It earns its place as a one-line summary but does not provide enough substance.

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 six parameters and no output schema, the description is far from complete. It omits the expected return format, how cost and response count are used, and what the human comparison entails. An agent would struggle to invoke this tool 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?

The schema has zero description coverage and the description explains none of the six parameters. Option_a and option_b are vaguely implied as the two outputs, but prompt, criteria, max_cost_cents, and required_responses are entirely unexplained.

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 core action: asking calibrated humans to compare two outputs. This distinguishes it from sibling tools focused on discovery, procurement, or QA review, though terms like 'calibrated humans' are somewhat specialized.

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 provides no guidance on when to use this tool versus alternatives such as me_qa_review or me_submit_outcome. It does not clarify whether this is for preference ranking, quality evaluation, or pairwise judgment.

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