Datasets List Columns For Table

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered, but the description adds nothing beyond that — no indication of whether table_id must come from a prior sync/list call, how large result sets behave, or what the response shape is. For a one-line definition there is no extra behavioral context.

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, front-loaded sentence with no filler — the lookup key is stated immediately. Brevity here shades into under-specification rather than padding, but structurally it is efficient.

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, and the core action is clear. What is missing is the parameter's provenance/format and any routing versus the column-listing siblings, which a single-parameter tool of this type could reasonably supply.

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%, so the description carries the full burden for the single required parameter. It only restates the name ('by its tableId') without saying where a valid tableId comes from, its format, or whether it must already be synced.

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 specific verb and resource ('List columns for a warehouse table') plus the lookup key, which is a clear purpose. It implicitly scopes to warehouse tables rather than data-model or workbook columns, but it never names the close siblings datasets_list_data_model_columns or elements_get_element_columns, so the agent must infer the boundary.

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 offers no when-to-use guidance, no prerequisites, and no alternatives. With siblings like datasets_list_data_model_columns and datasets_get_data_model_spec in the same namespace, an agent gets no help choosing between them.

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