df_list_dimension_groups

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds a clarifying parenthetical ('shared reference hierarchies') but discloses no further behavioral traits such as pagination, caching, or return format. With annotations present, the bar is lower, and the description adds minimal value beyond them.

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, efficient sentence with no wasted words. The core action and scope are front-loaded. It is appropriately terse for a list operation.

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?

For a list tool with annotations covering safety, the description is adequate but minimal. It does not mention pagination, language, or cache parameters, though these have defaults and might be inferred. The lack of an output schema means return structure is not specified, but for a list operation this is acceptable. Given the many siblings, a bit more differentiation would help, but it is not critically incomplete.

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 only 33% – only project_id and version_id have descriptions. The description does not compensate for the missing parameter documentation (page, language, page_size, use_cache). It provides no additional meaning about these parameters, and since coverage is low, the description should fill the gap but does not.

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 a specific verb ('List') and a specific resource ('dimension groups') with a scope ('of a version'). It distinguishes itself from siblings like df_get_dimension_group (which likely retrieves a single group) and df_list_fact_tables (a different entity). The purpose is unambiguous.

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 implies usage context (listing dimension groups for a version) but does not explicitly state when to prefer this tool over alternatives like df_get_dimension_group or other list tools. There are no exclusions or alternative routing, so the guidance is only implied, not explicit.

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