Find Korean model names

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only that this is autocomplete-style lookup and that output feeds another tool; it omits matching semantics (prefix vs substring, case sensitivity) and any default for limit.

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?

Two short sentences, zero filler, with the purpose front-loaded and the downstream usage second. Every clause earns its place.

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 no output schema, the description should describe the return shape; it only implies the results are usable as filter values for search_korean_cars. For a simple read-only lookup with annotations covering safety, this is adequate but leaves return format and limit behavior unexplained.

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 0% for two parameters. The examples ('sorento', 'gv70') do clarify what belongs in 'search', but 'limit' is completely undocumented in both schema and description, leaving half the parameters ambiguous.

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 verb and resource ('Autocomplete model names across brands') and grounds it with concrete examples ('sorento', 'gv70'), so an agent knows exactly what this returns. It differentiates itself from the sibling chinese_models via the Korean scope in the name, though it never explicitly contrasts the two.

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 sentence 'Use the result to filter search_korean_cars' explicitly routes the agent into the correct workflow and names the consuming sibling. There is no when-not guidance (e.g. when to skip autocomplete and search directly), which keeps it short of a 5.

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