df_get_dimensions

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

Annotations already declare the operation is read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond annotations by noting that dimension ids are stable and that connected_source is present only when bound to a database. It does not discuss cache behavior, but the annotation coverage lowers the burden.

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 two concise sentences with the main action front-loaded. The second sentence adds relevant details about return fields without unnecessary fluff.

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 simple read-only getter, the description covers the core purpose and some return-field semantics. However, there is no output schema, and the description omits details about the language and cache parameters, which matter for expected results. It is adequate but not fully complete.

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 coverage is only 50%, with project_id and version_id described but language and use_cache left undocumented. The description does not compensate for these gaps or clarify how language or caching affects results. It adds no parameter-level 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 clearly states the tool gets all dimensions of a project version, with a specific verb and resource. It also adds useful detail about the returned id and connected_source fields, but it does not explicitly distinguish this tool from closely related siblings like df_get_dimension_group or df_list_dimension_groups.

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 gives no guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. The only implied usage is that it fetches dimensions, but it does not clarify when to choose df_get_dimensions over related tools.

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