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transkribus-mcp-server

by lazyants

Get Model Training Data

transkribus_model_get_train_data
Read-onlyIdempotent

Retrieve training data for a Transkribus model based on its type and ID, enabling analysis or reuse in training workflows.

Instructions

Get the training data for a model by type and ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesModel type (e.g. htr, la, ocr)
idYesResource ID
indexNoStart index (0-based)
nValuesNoNumber of values to return
Behavior2/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. However, the description does not disclose pagination behavior implied by the optional 'index' and 'nValues' parameters, nor does it describe the return format. For a read operation with pagination, more transparency is expected.

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

Conciseness4/5

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

The description is a single, short sentence with no superfluous words. However, it is somewhat terse and could be more informative while remaining concise.

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?

Given the presence of 4 parameters (including optional pagination), no output schema, and many closely related sibling tools, the description is insufficient. It omits key details about pagination, the nature of 'training data', and how this tool differs from similar ones like transkribus_model_get_train_data_docs or transkribus_model_get_train_data_stats.

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 all parameters, so the baseline is 3. The description adds no extra meaning beyond 'by type and ID' – it does not clarify the purpose of the optional pagination parameters or provide examples.

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

Purpose4/5

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

The description clearly states the verb 'Get' and the resource 'training data', and specifies identification by 'type and ID'. However, it lacks differentiation from sibling tools like transkribus_model_get_train_data_docs or transkribus_model_get_train_data_stats, which have similar purposes.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools for getting training data (e.g., for docs, stats), the description should indicate the appropriate context or exclude other usages.

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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