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

Annotations already declare readOnlyHint=true, and the description only restates the HTTP verb via 'GET /api/nomenclature/languages', which adds little. It does usefully disclose the return shape (code, name), which the missing output schema would otherwise leave unknown.

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 tight sentence plus a short endpoint reference; the resource scope and return fields are front-loaded. The raw endpoint path is slightly redundant with the name/annotations but remains compact.

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 simple read-only nomenclature lookup with full schema coverage, the description covers what the tool returns (code, name pair) and what it represents, compensating for the absent output schema. Only explicit usage guidance is missing.

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 description coverage is 100% and the single cif parameter is fully documented there, including its source (oblio_list_companies) and format. The description adds no parameter-level meaning, so 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?

States a specific resource: 'foreign languages a company can issue documents in', plus the returned fields (code, name). It is clearly distinguishable from sibling list tools such as oblio_list_vat_rates or oblio_list_series, though the verb ('list') is only implied by the name rather than stated.

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 phrasing 'languages a company can issue documents in' implies the use case (selecting a language when issuing a document), but there is no explicit when-to-use statement, no prerequisites, and no mention of alternatives. Usage is inferable rather than stated.

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