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transkribus-mcp-server

by lazyants

Compute WER

transkribus_recog_compute_wer
Read-onlyIdempotent

Compute Word Error Rate (WER) between reference and hypothesis transcripts for a document, optionally within a specified page range.

Instructions

Compute the Word Error Rate for a document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collIdYesCollection ID
docIdYesDocument ID
pagesNoPage range (e.g. "1-5")
refNoReference transcript identifier
hypNoHypothesis transcript identifier
keyNoTranscript key
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, indicating a safe read-only operation. The description adds no further behavioral context beyond the stated purpose, which is acceptable given annotation coverage but misses an opportunity to clarify return values or side effects.

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

Conciseness3/5

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

The description is extremely concise (5 words). While not verbose, it under-specifies the tool's behavior given 6 parameters and no output schema. It could be slightly longer to improve clarity without being redundant.

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 no output schema, the description should at least mention the return type or format. It does not address what the tool returns. Additionally, the complex parameters (ref, hyp, key) are not explained in context. The rich annotations partially compensate, but overall completeness is lacking.

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?

The input schema has 100% description coverage for all 6 parameters. The description does not add any extra meaning beyond what the schema provides. Baseline score of 3 is appropriate as 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 clearly states the action (Compute) and the resource (Word Error Rate for a document). However, it does not differentiate from sibling tools like transkribus_recog_compute_error_rate or transkribus_recog_compute_wer_tasas, which could cause confusion.

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 (e.g., compute_error_rate, compute_wer_tasas). The description lacks context for usage scenarios or prerequisites.

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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