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transkribus-mcp-server

by lazyants

Get Training Data Documents

transkribus_model_get_train_data_docs
Read-onlyIdempotent

Retrieve the documents used as training data for a model by specifying the model type and ID, with pagination options.

Instructions

Get the documents used as training data for a model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesResource ID
typeYesModel type (e.g. htr, la, ocr)
indexNoStart index (0-based)
nValuesNoNumber of results (-1 for all)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv4.0.0
    • addedInput schema / properties / index / default
      Added value: +0
    • changedInput schema / properties / index / description
      Previous value: -"Start index"New value: +"Start index (0-based)"
    • changedInput schema / properties / index / minimum
      Previous value: --9007199254740991New value: +0
    • addedInput schema / properties / nValues / default
      Added value: +-1
    • changedInput schema / properties / nValues / description
      Previous value: -"Number of values"New value: +"Number of results (-1 for all)"
  2. Changed1 schema field changedv3.0.0
    • addedInput schema / properties / type / pattern
      Added value: +"^[^/\\s]+$"
  3. First observedv2.1.1

TDQS

C2.9/5.0
Behavior2/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, covering the safety profile. The description adds no further behavioral context such as pagination behavior, return format, or permission requirements, so it provides little beyond the structured annotations.

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 front-loaded sentence with no wasted words, which is efficient. It is appropriately sized for a simple read operation, though the extreme brevity leaves other dimensions underspecified.

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

Completeness3/5

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

For a simple getter with full schema coverage and annotations covering the safety profile, the description is minimally sufficient. However, it omits pagination context for the index and nValues parameters and does not distinguish this tool from its many close siblings, leaving ambiguity an agent must resolve elsewhere.

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 description coverage is 100%, so all four parameters are already documented in the input schema. The description adds no parameter-specific meaning, which matches the baseline of 3 when the schema does the heavy lifting.

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 names a specific verb ('Get') and resource ('documents used as training data for a model'), making the basic purpose clear. It does not explicitly differentiate itself from sibling tools like transkribus_model_get_train_data or transkribus_model_get_train_data_stats, so it stops short of a 5.

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 offers no guidance on when to use this tool versus the closely related transkribus_model_get_train_data, transkribus_model_get_train_data_stats, or transkribus_model_get_validation_data_docs. Usage context is only implied by the tool name and must be inferred by the agent.

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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