denmark_get_company

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

Annotations already cover read-only, open-world, and idempotent behavior, so the description adds valuable context beyond these: it specifies the CVR format handling ('DK prefix auto-removed') and the effect of the 'full' parameter on returned data ('complete data with production units and owners'). This enhances understanding of tool behavior without contradicting 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 front-loaded with the core purpose and efficiently structured in two sentences: the first covers the action and primary parameter, the second explains the optional parameter's effect. Every sentence adds value without redundancy, making it highly concise and easy to parse.

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?

Given the tool's moderate complexity (2 parameters), rich annotations (read-only, open-world, idempotent), and the presence of an output schema, the description is complete: it covers the key operational details (CVR handling, full parameter effect) without needing to explain return values or safety aspects already covered by structured data. It adequately supports agent decision-making.

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?

With schema description coverage at 50% (only 'cvr' has a description, 'full' does not), the description compensates well: it explains the 'cvr' parameter's format ('8-digit CVR number, DK prefix auto-removed') and the 'full' parameter's impact ('full=true for complete data with production units and owners'), adding meaningful semantics beyond the minimal schema. This addresses the coverage gap effectively.

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 clearly states the specific action ('Get company'), resource ('by 8-digit CVR number'), and scope ('DK prefix auto-removed'), distinguishing it from sibling tools like denmark_search_companies which searches rather than retrieves by specific identifier. It explicitly mentions the return behavior ('Returns summary by default; full=true for complete data'), providing precise operational context.

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 provides clear context for when to use this tool ('Get company by 8-digit CVR number') and implies when not to use it (e.g., not for searching by phone or production units, which are covered by siblings like denmark_search_by_phone). However, it doesn't explicitly name alternatives or state exclusions, such as when to use denmark_get_by_pnumber instead for P-number lookups.

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