List dimension values

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

No annotations are provided, so the description carries the burden. It discloses that results include exact values and counts, and implies a read-only listing operation, but does not state permissions, side effects, rate limits, or error behavior. The output schema likely covers return structure.

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 tightly written sentences with no waste. The core action and the pre-filtering usage rule are both 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?

The tool is simple, has one required parameter, and has an output schema, which reduces what the description must cover. However, it leaves out the set of valid dimensions and any behavioral safety context, which an agent may need before invoking it correctly.

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 explain the dimension parameter. It identifies it as a filter dimension and gives a 'priority' example, but does not enumerate valid dimensions or describe the accepted format beyond the example.

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: list the exact values available for a filter dimension, including case counts. The purpose is clear, but it does not explicitly differentiate itself from sibling tools such as counter_value_distribution.

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?

Gives clear usage context: call this before filtering, plus a concrete example showing that the exact label must be used rather than a formatted numeric label. It does not name alternatives or when-not-to-use conditions.

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