transkribus_recog_train_htr_citlabTrain CITlab HTR models for a collection by providing collection ID and training configuration.
Start CITlab HTR model training for a collection.
| Name | Required | Description | Default |
|---|---|---|---|
| collId | Yes | Collection ID | |
| config | Yes | Training configuration parameters |
Changes observed during successful MCP inspections.
v2.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate non-read-only, non-destructive, non-idempotent, and open world. The description adds no behavioral information beyond these annotations, such as duration, side effects on collection, or that training creates a new model. The lack of additional context leaves the agent uninformed about the tool's behavior.
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, which is concise but lacks important details such as the return behavior or the nature of the 'config' object. It is front-loaded with purpose but insufficiently informative for a complex training 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 no output schema and the complexity of starting a training job, the description should mention that it triggers an asynchronous job, what the return value indicates, or how to monitor progress. The current minimal text leaves significant gaps for an agent to correctly use the tool.
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?
The input schema has 100% description coverage, with 'collId' described as 'Collection ID' and 'config' as 'Training configuration parameters'. The description adds no extra meaning beyond the schema, so it meets the baseline but does not enhance parameter understanding.
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 'Start CITlab HTR model training' for a collection, with a specific verb and resource. It distinguishes from siblings by naming 'CITlab', which differentiates it from other training tools like 'transkribus_pylaia_train' or 'transkribus_recog_train_la2'.
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 or when not to use this tool, nor does it mention prerequisites or alternatives. There is no context about required data states, collection readiness, or comparison with sibling training tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.