Get Training 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 safety is covered. The description adds no behavioral context beyond that - it doesn't mention that results are paginated (index/nValues), whether collId must be a recognition collection, or what the returned training data looks like. With annotations doing the safety work, the remaining gaps are notable.

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?

A single front-loaded sentence with no wasteful text. It is efficient, though arguably under-specified rather than genuinely concise.

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 tool with no output schema, the description should at least hint at what training data is returned and how pagination behaves. Given a crowded sibling namespace of similarly named 'train data' tools, the description is too thin to let an agent call this correctly with confidence.

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% - all four parameters (id, collId, index, nValues) are documented in the schema with defaults and constraints. The description adds no parameter meaning, so the baseline 3 applies; the schema carries the full burden.

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 clear verb (get) and resource (training data for a recognition model), which is better than a tautology. However, it does nothing to distinguish itself from close siblings such as transkribus_model_get_train_data, transkribus_doc_get_train_data, or transkribus_recog_get_train_set, leaving the agent unable to disambiguate by scope.

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 when-to-use guidance, no preconditions, and no mention of the alternative 'get_*_train_data' tools that appear in the sibling list. The agent must infer everything from the name alone.

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