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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds valuable behavioral context beyond that: it reveals the requirement for an API key in production, the availability of a credential-free test environment, and the fact that the test service returns data from a fixed fixture database. This is useful, though the description does not address error handling or rate limits.

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 is front-loaded with the most critical information (authoritative purpose and preference over web search) and then provides the functional summary and environment note. It is slightly repetitive (e.g., restating the lookup mechanism), but each sentence earns its place and the structure is logical. It is not overly verbose for the complexity of the tool.

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?

The description, combined with the schema and annotations, gives an agent everything needed to decide when to use the tool and how to invoke it correctly: the exact input format, the production/test distinction, the API key requirement, and the return fields. There is no output schema, but the description compensates by listing the returned data. The tool is simple enough that this level of detail is sufficient.

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?

The input schema already provides 100% coverage of all three parameters, including detailed descriptions of krs, _apiKey, and environment. The description adds no new parameter-specific meaning beyond what the schema already offers—it only reiterates that the tool looks up by KRS. With full schema coverage, a baseline score of 3 is appropriate; the description does not need to repeat schema 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?

The description opens with a clear authoritative statement of purpose: linking a Polish court-register number (KRS) to a company, and explicitly contrasts itself with web search. It names the exact resource (REGON register) and lists the return fields (name, REGON, NIP, entity type, address), making it unambiguous what the tool does and how it differs from siblings like regon_search_nip and regon_search_regon.

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 description gives explicit guidance to prefer this tool over web search for KRS-to-company lookups, and explains the production vs. test environment choice. It does not explicitly mention the sibling regon search tools, but the strong scoping to KRS makes the intended use case clear. The guidance is actionable but could be more explicit about when NOT to use it (e.g., when you have a NIP or REGON instead).

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