search_accredited_labs

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

No annotations are provided, so the description carries the full burden. It discloses the data source (knab.go.kr) and that no API key is needed. However, it does not mention rate limits, authentication, or error handling. For a search tool, these are less critical, but the description is adequate.

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 sentences with no wasted words. The first sentence clearly states the action and criteria; the second adds return fields and data source. Front-loaded and efficient.

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 no output schema, the description lists returned fields (accreditation number, name, category, scope fields, validity end date). It also notes the data source and no API key. Missing details like sorting or pagination behavior, but overall complete for a search tool.

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%, so description must compensate. It explains 'query' as free-text and 'category' as accreditation category, which adds meaning beyond the enum. It implies pagination via 'paginated list' but does not explain the 'page' and 'page_size' parameters or defaults. This partial compensation yields a score of 3.

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 uses a specific verb ('Search'), identifies the resource ('KOLAS-accredited laboratories'), and specifies the input methods (free-text query and accreditation category). It clearly distinguishes from sibling tools like 'get_kolas_statistics' and 'get_lab_details' by focusing on searching vs. statistics or details.

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 implies usage for searching by query and category, and mentions a paginated list. While it doesn't explicitly state when not to use it, the context of sibling tools suggests appropriate usage. It could be improved by including exclusions, but it is clear enough for an agent.

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