create_data_view

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

Annotations provide no safety hints (readOnlyHint=false, destructiveHint=false), so the description must disclose behavioral traits. It explains the `space` parameter but does not mention permissions, what happens if the data view already exists, whether it is idempotent, or any side effects. This leaves significant ambiguity for an agent.

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 (three short sentences) and front-loads the core purpose. Every sentence adds value: the first explains the primary action, the second lists optional parameters, and the third clarifies the `space` argument. No wasted words.

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 creation tool with one required parameter and three optional ones, the description covers the essential context: what it does, the index pattern example, and the optional fields. It does not mention error handling or prerequisites, but the output schema likely covers return values. Overall, it is complete enough for a competent agent to use the tool correctly.

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?

With 0% schema description coverage, the description compensates by explaining each parameter's role: index_pattern (with example 'logs-*'), name (display name), time_field (for time-series data), and space (targets a Kibana space by id). This adds meaning beyond the schema's bare field definitions.

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 tool's function: 'Create a Kibana data view over an index pattern' with a concrete example. This is specific and distinguishes it from sibling tools like list_data_views or describe_data_view, which serve different purposes.

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 implies the use case—creating a data view for an index pattern—and mentions optional settings for time-series data. However, it does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or prerequisites (e.g., that the index pattern must exist).

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