check_domain_terms

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

Annotations already declare readOnly/idempotent/closed-world, so safety is covered; the description goes well beyond them. It discloses the crucial caveat that a reported compound is not necessarily coined and may be ordinary Estonian (with a concrete example), that suggestions are spelling-similar rather than synonymous, what contains_glossary_term means, that proper nouns are skipped, and that the hosted server holds no glossary.

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?

Purpose is front-loaded and nearly every sentence adds distinct information: definitions, caveats, the suggestions warning, the glossary requirement, and the proper-noun exception. It is dense and the opening sentence's clause order makes it harder to parse than necessary, but there is no filler to cut.

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?

With an output schema present, return values need no explanation, and the description still covers the interpretive burden: what a hit means, what it does not mean, how to act on it, and the configuration dependency on a supplied glossary. Nothing an agent needs in order to call this correctly and interpret results 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 coverage is 100%, so the baseline is 3, but the description adds operational meaning the schema does not: the server has no glossary, so the caller must supply one via `glossary`, and absent it the result degrades to a pure unattested list. It also clarifies how `suggestions` (driven by suggest_cutoff) should be read — spelled alike, not synonymous — which changes how the agent interprets that parameter's effect.

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 first sentence names a specific verb and resource: it reports Estonian compounds that no lexicon or domain glossary vouches for, in text about an organisation's own systems. It also points at the related sibling check_compound_familiarity, so the agent can separate attestation checking from glossary comparison. The phrasing is convoluted ('compounds no lexicon or domain glossary vouches for, in Estonian you wrote about...'), which slows first-pass comprehension, but the substance is specific rather than tautological.

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 states when to act and when not to: where the compound names something the organisation has a term or identifier for, use theirs; otherwise leave it. It also explicitly warns that without a glossary this is only the unattested list and 'never on its own a reason to rewrite', which is a clear negative condition. Alternatives are named (check_compound_familiarity) and the glossary-passing requirement is spelled out.

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