df_get_data_mart_view

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds context about what information is returned (staleness, last refresh, status), which is useful. However, it does not disclose potential behaviors like cache usage (use_cache parameter) or whether the call may trigger a refresh, though the annotations cover the core safety aspects.

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, compact sentence that front-loads the core purpose and lists the key output attributes. Every word earns its place, and there is no redundancy or 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 read-only inspection tool with annotations covering safety, the description is mostly adequate. However, with no output schema and only 40% parameter coverage, the description could have clarified the meaning of data_mart_id, language, and use_cache, and how the returned 'status' and 'staleness' are represented. The lack of parameter semantics leaves some gaps for an agent deciding how to invoke 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?

Schema description coverage is only 40%, with project_id and version_id described but data_mart_id, language, and use_cache lacking descriptions. The description does not add meaning for these parameters beyond the schema. The tool's purpose implies data_mart_id identifies the target, but the description does not explicitly explain the parameters or their roles, so it does not compensate for the coverage gap.

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 states a specific verb ('Get') and resource ('physical view materialized for a data mart') and enumerates the attributes returned (existence, object type, database, status, staleness, last refresh). It is clear what the tool does, though it does not explicitly distinguish it from the sibling df_get_data_mart, which likely returns the data mart definition rather than its physical 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 description implies a read-only inspection use case (checking physical view details), but it does not explicitly state when to use this tool versus df_get_data_mart or other sibling tools. No exclusions or alternative routing are provided, so the agent must infer usage from the name and description.

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