Brreg Entity Detail

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds context by enumerating the returned fields (address, VAT, bankruptcy status, etc.), specifying the source ('Brønnøysundregistrene') and the license (NLOD 2.0), enriching the agent's understanding of what to expect. No contradictions with annotations.

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 well-organised: it states the primary action first, then lists the return fields, and ends with a use case and source. While it is a bit long (over 100 words), every sentence adds useful information, and there's no fluff. The list of fields is structured and easy to scan.

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?

An output schema exists, so return values are covered; the description adds the field list anyway for quick reference. It also mentions the source and license, and the one required parameter is fully described in the schema. Missing items like rate limits or data freshness are minor for a read-only, idempotent tool with an output schema.

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%: the org_number parameter has a description, a regex pattern, and concrete examples. The description only repeats the '9-digit' requirement without adding new semantics, so the schema already does the heavy lifting. 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 opens with a specific verb-resource pair ('Retrieve full details for a specific Norwegian company or organisation by its 9-digit organisation number') and lists the return fields, clearly distinguishing this detail endpoint from sibling tools like search, roles, and sub_units. It also names the data source, which adds specificity.

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?

It explicitly says 'Ideal for KYB (Know Your Business) verification of Norwegian entities', giving a clear use case. However, it does not mention when NOT to use this tool or point to alternatives (e.g., search to find an organisation number first), though the siblings are visible in the context. The use case alone provides sufficient guidance for an agent.

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