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

No annotations are provided, so the description carries the burden. It discloses the return data structure (ranked by attention score, fields like avgAttentionScore) and implies read-only through the verb 'get,' but it doesn't explicitly state safety, permissions, or any side effects. This is adequate but not exceptional.

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 well-structured with clear sections (WHEN TO USE, RETURNS), uses bullet points for readability, and every sentence earns its place. No fluff or redundancy.

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 simple one-parameter tool, the description is complete: it explains the purpose, provides use cases, and details the return fields (acting as a pseudo output schema). It lacks only explicit notes on edge cases or limitations, but it's sufficient for effective invocation.

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 includes a single required parameter campaign_id with a description 'Campaign identifier,' giving 100% schema coverage. The tool description does not add any additional parameter-level semantics beyond what the schema already provides, so 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 starts with 'Get per-creative attention breakdown for a campaign,' which combines a specific verb (get) with a clear resource (per-creative attention) and scope (for a campaign). This distinguishes it from sibling tools like get_attention_metrics or get_social_attention.

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 WHEN TO USE section explicitly lists three concrete use cases: A/B testing creative variants, identifying engagement drivers, and comparing aCPM. While it doesn't mention exclusions or alternative tools, the context provided is clear and actionable.

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