Datasets List Data Model Elements

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered structurally. The description adds nothing beyond that - no scoping, no pagination behavior, no note on what an 'element' is - so it earns little credit even against the lowered annotation-covered bar.

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 short sentence is appropriately sized and front-loaded with the verb, but the brevity reflects under-specification rather than discipline - key distinctions are simply absent.

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 explained, but the description leaves 'elements' undefined and says nothing about scoping or result size. For a tool sitting among many similar list operations, this is too thin to call correctly with confidence.

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 the single required parameter data_model_id, so the description carries the full burden and fails to define the parameter's format or origin. It adds no meaning beyond the parameter name itself.

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?

States a clear verb (List) and resource (elements in a data model), which is more than a tautology. However, 'elements' is vague and undefined, and the description does nothing to separate this from close siblings like datasets_list_data_model_columns or datasets_list_data_model_lineage.

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?

No when-to-use guidance, no prerequisites, and no mention of alternatives despite many sibling list tools. An agent gets no signal about when this tool is preferable to datasets_list_data_model_columns or datasets_get_data_model_spec.

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