df_get_dimension_group

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds value by disclosing exactly what the returned object contains (primary key, member dimensions, hierarchy levels, related fact tables), which is behavioral context beyond the annotations.

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?

One compact sentence that front-loads the purpose and then lists the output components. There is no redundancy or filler, making it easy to scan.

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 incomplete parameter schema coverage, the description should compensate more. It explains return contents well, but leaves language and use_cache semantics unexplained, and does not address potential error cases or prerequisites. Overall, an agent can call the tool correctly for the core use case, but there are meaningful gaps.

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 40%, and the description does not compensate. It does not explain the meaning of language, use_cache, or dimension_group_id beyond what is implied by the tool name. The two schema-described parameters (project_id, version_id) are straightforward, but the other three remain undocumented in both schema and description.

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 ('Get'), a specific resource ('one dimension group'), and enumerates its contents (primary key, member dimensions with hierarchy levels, related fact tables). This clearly differentiates it from siblings like df_list_dimension_groups, df_get_dimensions, and df_get_fact_table.

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 'Get one dimension group' makes it clear this is the tool to use when you have a specific dimension_group_id and need its details, as opposed to listing all groups. However, it does not explicitly name alternative tools or state when not to use it, so it earns a 4 rather than a 5.

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