list_data_views

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safe read nature is covered. The description adds the space-scoping behavior, which is useful, but does not disclose other behavioral traits such as pagination, ordering, or whether all views are returned across the entire stack.

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, front-loads the main action, and every word adds value. There is no redundant restatement of the tool name or schema fields.

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 list operation with one optional parameter, an output schema, and read-only annotations, the description covers the essential semantics: what is listed, what the parameter means, and the default behavior. No significant information gap remains.

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?

Although the schema has no descriptions and reported coverage is 0%, the description compensates by explaining the single 'space' parameter: it targets a Kibana space by id and defaults to the default space. This adds semantic meaning beyond the raw schema type and default value.

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 uses a specific verb and resource: 'List Kibana data views' and clarifies them as 'the datasets you can visualize.' This clearly distinguishes it from sibling tools like describe_data_view and create_data_view, which operate on a single view or create one.

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 intended use is implied by the phrase 'the datasets you can visualize' and the space-targeting comment, but there is no explicit mention of when to choose this over alternatives such as describe_data_view or search_dashboards. No exclusions or conditional guidance are provided.

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