get_kolas_statistics

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 and that the tool returns statistics. However, it does not mention response format, potential errors, or rate limits. For a simple read-only tool, the behavioral disclosure is adequate but not rich.

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 consists of two concise sentences with no wasted words. It starts with the core purpose and immediately adds the data source and requirement, making it efficient and front-loaded.

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 and no annotations, the description could be more complete. It states the output is counts per category per year but omits details like response structure, pagination, or external API dependencies. It is adequate but leaves gaps for an agent to infer.

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%, so the description must compensate. It only loosely connects 'per category per year' to the 'year' and 'category' parameters, but does not explain their formats, defaults, or the meaning of category values. The description adds minimal value beyond the schema's enum and pattern.

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 clearly states the tool returns annual KOLAS accreditation statistics (number of accredited organizations per category per year) and identifies the data source. It distinguishes itself from sibling tools ('get_lab_details' and 'search_accredited_labs') by being aggregate statistics vs. details or searching.

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 explicitly mentions a required API key ('Requires KOLAS_SERVICE_KEY') as a prerequisite. It implies use for obtaining aggregate statistics, but does not explicitly state when to use this tool over siblings or when not to use it.

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