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 of behavioral disclosure. It does disclose the return shape and the read-only intent ('Discover'). However, it does not mention that slow queries may return a pending operation with done:false and a path for get_operation, even though pollTimeoutSeconds references this behavior. This is a notable behavioral 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 three sentences: purpose with examples, downstream usage, and return shape. It is front-loaded, concise, and every sentence earns its place without unnecessary detail.

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 9 parameters and no output schema, the description needs to cover the result contract adequately. It provides the primary return shape, but omits the asynchronous pending-operation case (done:false / path / get_operation), which is relevant for correct invocation and result handling. Since the schema documents pollTimeoutSeconds, this is not fatal, but it leaves a gap.

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 100%, so the baseline is 3. The description adds useful context about dimension value examples and how values feed query_metrics filters, but it does not add substantial parameter-specific meaning beyond what the schema already provides.

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 and resource: 'Discover the actual values a dimension takes for a metric in a universe over a date range.' It gives concrete examples (Country codes, Platform names, FunnelName values, Place IDs), which clearly distinguish it from sibling tools like list_metrics, query_metrics, and get_operation.

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 tells the agent how to use the output: 'Use the returned values in query_metrics filters or to understand breakdown results.' This gives clear context for when the tool is valuable. It does not explicitly contrast with list_metrics or state when not to use it, so it falls slightly 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.