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

Annotations already declare readOnly, idempotent and closed-world, so the safety profile is carried structurally. The description adds genuine behavioral detail beyond that: results are aggregated as 'named in k of n answers' and it reports a separate count for answers naming the competitor but not you, which tells the agent what the output measures rather than merely that it is a read.

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?

It is a single dense sentence that front-loads the subject (which businesses) and then the metric. The trailing clause about competitors named without you is slightly compressed but every part carries information; nothing is padding.

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?

With an output schema present, the description needn't explain return shape, and it correctly spends its words on what the numbers mean (k of n, per-engine, named-not-you) and on scope (your site). This is sufficient for an agent to call the 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?

Schema description coverage is 100%, so both `site` (including the multi-site fallback behavior) and `cursor` are already fully documented in the schema. The description adds no parameter-level information beyond the implicit 'your site' framing, so the baseline 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 names a specific resource (businesses/domains co-named in AI answers with your site) and a specific breakdown (engine by engine), which is concrete enough for an agent to know what comes back. It does not, however, name or contrast with the obvious overlapping sibling get_google_competitors, so disambiguation is left to inference.

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?

Usage is only implied: an agent can infer 'use this when you want AI-answer competitors' versus google competitors. There is no explicit when-to-use, no exclusion, and no pointer to get_google_competitors or get_ai_answers as the alternative for a different question, which is a real risk given the sibling set.

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