get_attrib_values

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

With no annotations, the description carries the full burden. It discloses the response structure, server-side response cap (apply_response_cap), and NO_UNDO behavior, which are useful. However, it does not explicitly confirm the operation is read-only, nor does it explain potential pitfalls such as scene requirements or behavior on invalid attributes.

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 short and front-loaded, using bullets for clarity. However, the parenthetical 'add-geometry-export-and-measure' appears to be an internal branch or feature tag that adds noise without value to an AI agent selecting the tool.

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?

Given the 6-parameter schema and no output schema, the description is incomplete. It omits parameter meanings, usage scenarios, and error behavior. The return structure and response cap are disclosed, but an agent cannot confidently invoke this tool for a specific use case without additional information.

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 clarifies attrib_class accepted values and introduces owner/storage/tuple-size as dispatch concepts, but it does not explain the core parameters (ctx, node_path, attribute) or clarify the relationship between limit/offset and pagination. The return structure is stated, but parameter semantics remain largely underspecified.

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 the tool reads attributes with a specific dispatch mechanism (by owner/storage/tuple-size) and mentions native pagination, which goes beyond merely restating the tool name. However, it lacks a plain-language summary like 'get attribute values from a node' and does not explicitly distinguish itself from closely related siblings such as get_geometry_data or get_geo_summary.

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?

No guidance is provided about when to use this tool versus alternatives like get_geometry_data or get_parameter. The mention of native pagination implies use for large datasets, but this is not stated as a condition, and there are no exclusions or alternative tool references.

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