Get Training Data

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which cover safety and idempotency. The description adds no additional behavioral details (e.g., return format, pagination behavior, or required permissions), providing minimal extra value.

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, front-loaded sentence with no wasted words. It is as concise as possible while conveying the core purpose.

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 4 parameters and no output schema, the description lacks completeness. It does not explain what 'training data' comprises, how pagination works (index/nValues), or what the output looks like. The tool's role relative to model training is also unclear, leaving significant gaps for the agent.

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 100% with basic descriptions for all four parameters (collId, id, index, nValues). However, the description does not enrich parameter semantics or clarify their usage, so it does not exceed the baseline for full schema coverage.

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 verb 'Get' and resource 'training data' for a 'recognition model'. It is specific enough to convey the tool's purpose, but does not differentiate it from similar sibling tools like transkribus_recog_get_train_set or transkribus_model_get_train_data.

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?

There is no guidance on when to use this tool versus alternatives. It does not mention context, prerequisites, or situations where this tool is preferred over similar tools, leaving the agent without decision-making information.

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