Suggest Resume Search Keyword

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

With no annotations, the description must carry the behavioral burden; it conveys that this is a non-mutating suggestion/lookup over employer-side data and that the result is a set of phrases. It omits result count/limits, ordering, matching semantics (prefix vs substring), and language/locale assumptions.

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 sentence, front-loaded with the verb and purpose, with no filler. It could still have afforded a short second sentence of usage detail at negligible length cost.

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 single-required-parameter, no-output-schema utility tool, the description covers what goes in and what comes out at a reasonable level. Gaps around limits and downstream use are minor given the tool's simplicity.

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 0% — 'text' is documented only as a bare string. The description compensates partially by stating it is a 'partial keyword', which is meaningful added semantics, but says nothing about minimum length, casing, or multi-word behavior.

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 gives a specific verb ('suggest') plus the resource ('full search phrases for resume search') and the input ('a partial keyword'), which is enough to distinguish it from suggest_vacancy_search_keyword and the dict_* lookup siblings. The '(employer side)' note clarifies whose dataset is queried.

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?

Usage is implied: pass a partial keyword to expand into full phrases, clearly envisioning an autocomplete flow. There is no explicit when-not guidance and no mention of how these phrases relate to the search_vacancies/keyword-search flow or whether dict_skills should be preferred for enumerations.

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