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transkribus-mcp-server

by lazyants

Run Text2Image Matching

transkribus_recog_text2image_matching

Aligns recognized text lines to their corresponding image positions in a collection using a specified HTR model.

Instructions

Run Text2Image matching using a specific model in a collection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collIdYesCollection ID
modelIdYesModel/HTR ID
docIdYesDocument ID
pagesNoPage range (e.g. "1-5")
creditsNoCredits parameterAUTO
doNotDeleteWorkDirNoDo not delete work directory
preserveLineOrderNoPreserve line order
keepUnmatchedLinesNoKeep unmatched lines
useSourceLineFeedsNoUse source line feeds
addNotMatchedTextInLastLineNoAdd unmatched text in last line
useCurrentTranskriptNoUse current transcript
allowDoubleMatchingNoAllow double matching
reductionMethodNoReduction method
blockThreshNoBlock threshold
lineThreshNoLine threshold
Behavior2/5

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

Annotations indicate the tool is not read-only, not destructive, not idempotent, and open world. The description's single phrase 'Run Text2Image matching' does not disclose any behavioral characteristics beyond what annotations already imply—such as whether it creates a job, how long it takes, or error conditions. It adds no meaningful context.

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 sentence that is direct and concise. It wastes no words, but it is not structured with bullet points or sections. However, for a simple tool, the conciseness is appropriate.

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?

With 15 parameters and no output schema, the description is too brief. It does not explain what the matching process entails, what the output looks like, or how to interpret results. The tool is complex, and the description lacks necessary details for an agent to use it 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?

All 15 parameters have descriptions in the input schema (100% coverage). The description does not add any extra meaning or context beyond what the schema provides. Baseline is 3 because schema coverage is high, but the description fails to elaborate on parameter usage or relationships.

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 action ('Run') and the resource ('Text2Image matching') with the context of using a specific model in a collection. However, it does not distinguish this tool from similar sibling tools like 'transkribus_recog_text2image' or 'transkribus_recog_text2image_citlab', which share the same core resource.

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. There is no mention of prerequisites, when not to use it, or comparison to other tools. The agent is given no context for decision-making.

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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