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transkribus-mcp-server

by lazyants

Train Layout Analysis (CITlab)

transkribus_recog_train_la_citlab

Train a CITlab layout analysis model for a collection by providing the collection ID and training configuration parameters.

Instructions

Start CITlab Layout Analysis model training for a collection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collIdYesCollection ID
configYesTraining configuration parameters
Behavior2/5

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

The description states 'Start... model training', which implies a mutation, consistent with readOnlyHint=false. However, it does not disclose side effects (e.g., asynchronous job, credit consumption, required permissions) that go beyond what annotations provide. Annotations are minimal, so the description should offer more behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with no unnecessary words. It is front-loaded with the key action and resource.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite being a training tool with a nested 'config' object and no output schema, the description lacks details on the training process, return value, monitoring, and typical configuration. It is insufficient for an agent to understand how to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters ('Collection ID' and 'Training configuration parameters'). The description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Start'), the specific resource ('CITlab Layout Analysis model training'), and the context ('for a collection'). It distinguishes from sibling tools like transkribus_recog_train_htr_citlab and 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.

Usage Guidelines2/5

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, such as transkribus_recog_train_la2 or transkribus_la_analyze. It does not mention prerequisites, conditions, or typical use cases.

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

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