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

No annotations are provided, so the description carries the full burden. It discloses the nature of the action (getting a real human to rate), the output (overall rating, criteria scores, qualitative feedback, comparison notes), and the timing (before distribution). However, it does not mention potential latency, cost, or any asynchronous behavior that might be expected from involving a human, which would be valuable behavioral context.

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 two sentences, front-loaded with the action and purpose. Every sentence adds value: the first states what the tool does, the second specifies when to call it and what it returns. No unnecessary information or repetition.

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 description covers the tool's purpose, usage timing, and return values. An output schema is present, so the description need not elaborate on return structure. The only minor gap is not addressing practical constraints of using a real human (e.g., latency), but overall the description is complete for a tool of this 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?

The input schema provides 100% description coverage for all parameters, so the baseline is 3. The description reinforces the importance of targetDemographic ('matching your target demographic') and content ('your content'), but does not add further parameter-level detail beyond what the schema already provides.

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 verb ('Get a real human... to rate and react') and identifies the resource (a representative audience member matching a target demographic). It clearly distinguishes itself from sibling tools by emphasizing audience reaction prediction before A/B tests, ad spend, or distribution decisions, which is unique among the listed tools.

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 explicitly states when to use the tool: 'Call before A/B test commits, before ad spend, or before distribution decisions.' This provides clear usage context, but it does not mention when not to use it or explicitly name alternative tools, so it stops short of a full 5.

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