transkribus_model_get_train_data_statsRetrieve statistics about training data for a specific model by providing its type and ID. Use this to assess dataset composition and quality.
Get statistics about the training data for a model.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Resource ID | |
| type | Yes | Model type (e.g. htr, la, ocr) |
Changes observed during successful MCP inspections.
v3.0.0Input schema / properties / type / patternAdded value: +"^[^/\\s]+$"v2.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds no behavioral context beyond 'Get statistics' — it does not specify what statistics are returned, format, or pagination. For a read-only tool with no output schema, this is a significant gap.
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 sentence with no waste, but it is too sparse — every word is generic. It does not earn its place beyond stating the obvious. Could be restructured to include more context without becoming verbose.
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 tool's simplicity (2 required params, no output schema, safe read), the description is barely sufficient. However, the large number of similar sibling tools demands more detail to help the agent differentiate. Missing return value info and usage examples. The description is incomplete for effective tool selection.
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% (both parameters have descriptions in the schema). The description adds no additional meaning about parameters — for example, it does not explain what 'type' values are valid or how 'id' is used. Baseline 3 is appropriate since schema does the work.
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?
Description clearly states verb ('Get statistics') and resource ('training data for a model'). However, the tool name already implies this, and there is no differentiation from siblings like `transkribus_doc_get_train_data` or `transkribus_model_get_train_data`. The purpose is clear but generic.
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 on when to use this tool versus alternatives (e.g., `transkribus_model_get_train_data` or `transkribus_model_get_train_data_docs`). No prerequisites or context on required model type or ID. The description is insufficient for an agent to decide when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.