Update Data View

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

Goes well beyond the annotations by disclosing non-obvious behavior: a time_field/index_pattern mismatch results in a no-op ('nothing changes'), a pattern matching no index is accepted with field_count 0, the time field cannot be removed, a defaulted name stays put, and existing dashboard panels retain the old pattern until rebuilt. This is exactly the kind of mutation consequence an agent needs.

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?

Front-loads the purpose and the id source, then proceeds through edge cases in a logical order. It is dense and slightly long, but nearly every clause communicates a distinct constraint, so little is wasted.

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 5-param mutation with 0% schema coverage, the description covers mutability semantics, validation, no-op conditions, and side effects on dependent panels. Output schema exists, yet the description's brief return-value listing (id, name, index_pattern, time_field, field_count) reinforces the post-update state without being redundant.

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 carry the load, and it does: it identifies view_id's origin, illustrates index_pattern ('logs-*'), constrains time_field to a date field of the view, explains name's default-retention behavior, and defines space as a Kibana space id defaulting to the default space. All five parameters gain meaning beyond the raw schema.

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+resource ('Edit an existing data view in place, by id') and immediately disambiguates from siblings by pointing to list_data_views as the id source and update_panel for dashboard rebuilds. An agent can distinguish this from create_data_view and describe_data_view without opening any schema.

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?

Gives clear context: partial-update semantics ('Only the fields you pass change'), where the id comes from, and routes to update_panel when panels need rebuilding. It stops short of an explicit when-not-to-use or a prerequisite/permission statement, so it is strong but not exhaustive.

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