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

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the description's job is to add matching behavior — and it does: case-insensitive substring matching, exact-match ranking first, remaining results sorted ascending by code, capped at 10 results. The result cap and ranking order are genuinely useful behavior an agent cannot get from the annotations. It does not say what a zero-result response looks like.

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?

One sentence, front-loaded with the match semantics, then ranking, then the result cap. Every clause carries information an agent needs; nothing is redundant with the schema or annotations.

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 one-parameter read-only search with annotations and no output schema, the description supplies matching rules, ordering and the 10-result limit, which is close to everything needed to call it correctly. Only edge-case behavior (no match, how results are shaped) is left implicit.

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 0%, so the description carries the full burden for the single query parameter — and it does explain that the value may be either a company code or a company name and is matched as a case-insensitive substring. It omits the 1–100 character length constraint, but that is a minor gap against otherwise strong semantics.

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 states a specific action on a specific resource: case-insensitive substring matching against company code or company name. It is clearly distinct from the siblings (revenue and industry functions), though it never names them explicitly. Purpose is unambiguous from the first clause.

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 this is the lookup entry point for identifying a company before calling get_company_revenue or get_monthly_revenue_history, but the description never says so. There are no explicit when-to-use, when-not-to-use, or alternative-naming statements.

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