list_dimension_values

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering the safety profile. The description adds that it discovers values that 'actually' exist in the data, implying a data-derived enumeration rather than a static list, which is useful context. It does not disclose sampling, time-window behavior, or result shape beyond this.

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 a single, front-loaded sentence with no wasted words. The core purpose and illustrative examples are delivered immediately.

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?

An output schema exists, so return values need not be described, and annotations cover the safety hints. However, for a tool with two undocumented parameters and many sibling analytics tools, the description omits how `days` and `dimension` work and provides no guidance for selecting this tool over alternatives. It is too sparse to be complete for reliable invocation.

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% for two parameters (`days` and `dimension`), so the description carries the full burden of explaining them. It mentions the concept of a dimension and gives examples but never explains the `dimension` parameter's accepted values or the `days` parameter's role in limiting the time window. This is a significant gap for correct invocation.

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 states a specific verb and resource: 'Discover which values a dimension actually has,' with examples of real page paths and UTM sources. It is clear enough to distinguish from metric-oriented siblings like list_metrics or query_metrics, though it does not explicitly name an alternative tool.

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?

Usage is implied by the phrase 'actually has (e.g. real page paths, real UTM sources),' suggesting it is for enumerating existing dimension values rather than querying metrics. However, there is no explicit guidance on when to use this versus breakdown, query_metrics, or other sibling tools, and no exclusions or prerequisites are given.

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