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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds genuinely new behavior — the fallback basis logic and the fact that the response reports which basis was used, plus what fields come back. It stops short of noting pagination/ordering or how many peers exist by default.

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?

Two sentences, no filler, and the comparability rule is front-loaded ahead of the payload description. Every clause carries information an agent needs.

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 no output schema, the description does the work of describing the return shape (signal totals, top dimensions, stated basis), which is the key thing an agent needs. Minor gaps remain around default limit behavior and result ordering, but nothing critical is missing for a read-only lookup.

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 slug, limit, and context are already fully documented in the schema, including the notable detail that context is never used for ranking. The description adds no parameter-level meaning beyond that, which is the baseline 3 case.

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?

States a specific resource (companies comparable to a given company) plus its selection rule (same sub-sector when data supports it, same industry otherwise) and the payload contents (signal totals, top dimensions). An agent can tell it apart from the other company_* tools by the 'peers' framing, though it never names a sibling to contrast against.

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 implied by the name and the selection rule — you call it when you want comparable companies for a slug — but there is no explicit when-to-use/when-not guidance and no named alternative (e.g. find_related, company_dimensions, find_company_insights) to route between.

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