transkribus_recog_get_validation_gt_by_htrRetrieve validation ground truth data for an HTR recognition model to compare against predictions and assess accuracy.
Get validation ground truth data for a recognition model.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Resource ID | |
| index | No | Start index (0-based) | |
| collId | Yes | Collection ID | |
| nValues | No | Number of results (-1 for all) |
Changes observed during successful MCP inspections.
v4.0.0Input schema / properties / index / descriptionPrevious value: -"Start index"New value: +"Start index (0-based)"Input schema / properties / index / minimumPrevious value: --9007199254740991New value: +0Input schema / properties / nValues / descriptionPrevious value: -"Number of values"New value: +"Number of results (-1 for all)"v2.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds nothing beyond that — no mention of pagination behavior implied by index/nValues, no note on what 'ground truth' contains or whether it requires model ownership.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short, front-loaded sentence with zero filler. It is arguably too terse for the tool's ambiguity, but nothing is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A read-only tool with a fully documented schema and no output schema, so the description is minimally viable. It still omits pagination semantics and disambiguation from sibling validation-data tools, which an agent would need to pick correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each of id, collId, index and nValues documented, so the baseline is 3. The description adds no interpretation of these parameters (e.g. that nValues=-1 returns all) beyond what the schema already says.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource ('Get validation ground truth data for a recognition model'), and the title adds the HTR-ID scoping that distinguishes it from the model/doc variants. However, the description never distinguishes it from close siblings like transkribus_model_get_validation_data or transkribus_doc_get_validation_data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance, no prerequisites, and no naming of alternatives despite several near-identical validation-data siblings. The agent must infer usage entirely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.