Get Facet Values

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'get' and 'discovering', which implies a read operation, but does not explicitly state safety, side effects, authentication needs, or return format. This is a significant gap.

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 two concise sentences. The first sentence states the core function, and the second adds practical context. There is no fluff or redundancy.

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 and no annotations, the description should clarify what the tool returns and how to use the optional parameter. It lacks details on return structure, default behavior when 'facet' is null, and any limitations. The description is minimal and leaves the agent guessing.

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?

The input schema has one parameter 'facet' with no description, and the schema description coverage is 0%. The tool description does not explain how to use the 'facet' parameter, what valid values are, or whether it is required. It only mentions types of facets without linking them to the parameter.

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 'gets available filter values for categorizing datasets' and lists examples like publishers, keywords, and themes. This specific verb+resource pairing distinguishes it from siblings that deal with datasets/records rather than facets.

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 phrase 'Useful for discovering publishers, keywords, themes, or other facets to refine dataset searches' gives clear context for when to use this tool. It does not explicitly name alternatives or exclusions, but the use case is well implied.

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