Get Validation Data

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 description does not need to repeat safety traits. However, it adds minimal behavioral context beyond the annotations, such as explaining pagination via index/nValues or describing the nature of the returned validation data.

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 concise sentence that front-loads the core purpose. No extraneous words or redundancy.

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?

Despite rich annotations and full schema coverage, the description lacks explanation of the output (no output schema), pagination behavior (index/nValues parameters), and differentiation from sibling tools. It feels incomplete for a tool with 4 parameters and no output schema.

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 coverage is 100% with all 4 parameters having descriptions. The tool description does not add any additional meaning or context beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 action ('Get'), the resource ('validation data'), and the key identifiers ('by type and ID'). It is specific enough to distinguish the tool from generic model retrieval, but does not explicitly differentiate from sibling tools like transkribus_model_get_validation_data_docs or transkribus_model_get_validation_data_stats.

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 provides no guidance on when to use this tool versus alternatives (e.g., model_get_validation_data_docs, model_get_validation_data_stats). There is no mention of prerequisites, context, or exclusions, leaving the agent to infer usage without support.

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