describe_data_view

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

Annotations already communicate the read-only safety profile, and the description adds useful behavioral context: `space` targets a Kibana space by id and defaults to the default space. The output schema also covers return shape, so the transparency burden is reasonably met.

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 compact and front-loaded: one clear purpose sentence, one practical usage sentence, and one terse parameter note. There is no redundant filler.

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 low-complexity, read-only metadata tool with an output schema and annotations, the description covers the trigger situation and the space default well. It is slightly incomplete only because the format of the `data_view` parameter is not explicitly specified.

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 must compensate. It explains `space` well, but it does not clarify whether `data_view` expects an ID, name, or title. The tool name and first sentence imply it identifies a data view, but this is only partial parameter guidance.

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 opens with a specific action and object: 'Get a data view's fields and types.' It also gives a concrete use case ('Call this before creating a visualization so you use real field names'), which clearly distinguishes it from siblings like list_data_views and create_data_view.

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 instruction 'Call this before creating a visualization' provides an explicit context for when to use the tool. It does not enumerate exclusions or alternative tools, but the guidance is clear enough for an agent to select this tool appropriately.

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