lakeview_dashboard_list

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

The description only states the basic action but does not mention behaviors like pagination (page_size, page_token) or the effect of the `show_trashed` parameter. With `readOnlyHint` already present, the description adds minimal additional transparency.

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 sentence—conciseness is achieved but at the expense of essential information. It is under-specified for a tool with three parameters.

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?

Despite a simple tool with only three optional parameters and an output schema, the description fails to explain parameter semantics. However, the output schema (not shown) may compensate for return structure. The description is 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?

The schema has 0% description coverage, and the tool description does not explain any of the three parameters (page_size, page_token, show_trashed). The agent must infer their meaning from names alone, which is insufficient.

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 verb 'List' and the resource 'Lakeview dashboards in the workspace.' It distinguishes from sibling tools like `lakeview_dashboard_get` (single dashboard) and `lakeview_dashboard_trash_list` (trashed dashboards) by naming the scope implicitly.

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 guidance is provided on when to use this tool versus alternatives such as `lakeview_dashboard_trash_list` for trashed dashboards or `lakeview_dashboard_get` for a specific dashboard. The agent receives no contextual cues.

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