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

With no annotations, the description carries the burden of explaining behavior. It discloses output structure, defines key metrics, and even provides the aCPM formula. It implies read-only behavior via 'Get' but does not explicitly state side-effect-free operation or any rate limits, though these are less critical for a data retrieval 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 uses clear section headers (WHEN TO USE, RETURNS, formula) and is well-organized. The opening includes a slightly promotional sentence about FEIN edge AI, which adds some fluff but is not waste; overall it is efficient and scannable.

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 tool has a single parameter and no output schema, the description is thorough: it explains the return structure with nested fields, defines the units (0-1 scores, seconds), and provides the aCPM formula. This is complete enough for an agent to understand what to expect.

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% for the single parameter campaign_id, with a basic description 'Campaign identifier'. The tool description adds no extra semantic detail about the parameter beyond what the schema already provides, so the baseline of 3 applies.

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 action ('Get edge AI attention metrics for a campaign') and identifies the unique FEIN-powered aspect. It distinguishes itself from siblings like get_campaign_performance or get_social_attention by specifying the type of attention metrics and the FEIN technology.

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 provides clear contexts such as measuring actual attention, comparing aCPM vs CPM, and getting face/dwell/emotion data. However, it does not explicitly mention when not to use this tool or name alternatives, so it stops short of full exclusions.

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