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

Annotations already declare this as a read-only, idempotent, closed-world operation, so the safety profile is covered. The description adds that results are ids for fetch (a two-step retrieval pattern) and that queries work in any language, which is useful. However, it doesn't describe limits, pagination, ranking behavior, or the shape of results, leaving some behavioral gaps.

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 a dense but front-loaded paragraph that starts with the purpose and then details corpus contents, return type, and query tips. Every sentence contributes information; it is slightly packed but well-structured. No filler.

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 a single-parameter search tool with full schema coverage, annotations covering safety, and an output schema (so return values needn't be explained), the description provides enough context: what's searchable, that results are ids for fetch, and language flexibility. It could mention how to use the resulting ids with fetch or any result limits, but it's largely complete.

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%, and the single 'query' parameter is well-documented in the schema itself with examples of what to search for. The description reinforces this by mentioning any-language queries and naming the canton for rules, but adds little beyond the schema. Baseline 3 is appropriate.

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 names a specific verb (Search) and a well-defined resource (Clino's documents on employing household help in Switzerland), then enumerates the corpus contents (one document per canton, employer fact sheet, official figures). This distinguishes it from siblings like get_canton_rules and get_employer_guide, which are clearly retrieval-by-key rather than search.

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 explains what the tool returns (ids for fetch) and gives a clear usage tip: 'name the canton for canton rules' and 'Queries in any language'. This implies when this tool is appropriate (free-text discovery) versus siblings like fetch or get_canton_rules (direct retrieval). It doesn't explicitly exclude use cases or name alternatives, but the routing signal via 'ids for fetch' is strong.

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