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

Annotations already declare readOnly/idempotent/openWorld=false, and the description goes well beyond them: it discloses the free-account auth requirement, the ~200-match cap, the default ordering, the A–Z continuation across pages, and that each answer carries order/max_page. This is rich behavioral disclosure an agent cannot get from structured fields alone.

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?

Front-loads the auth requirement, then purpose, then filtering/pagination behavior, then return fields. Dense but every clause carries information; only the return-field list is slightly list-like.

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 compensates by enumerating the returned fields (id, slug, name, kind, domain, HQ, industry, size band, editions), and it covers auth, result caps, and pagination. An agent has what it needs to call and interpret the tool.

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%, so the schema documents q, page, and country. The description still adds value by explaining the no-q path and its ordering/pagination semantics, though it doesn't restate the ISO-3166 or page-size details.

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 verb+resource (search canonical companies by name, full-text) plus scope (best 200 matches, optional HQ-country filter). It distinguishes the search behavior clearly but never names the sibling it replaces, so an agent must infer its relationship to get_company, find_prospects, or semantic_search.

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?

Gives conditional behavior for the q-absent case ('most active first') and the country filter, which implies usage. However it never names alternatives or states when to prefer this over get_company, find_prospects, or semantic_search, leaving the routing decision to inference.

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