transkribus_recog_compute_error_rateCompute the error rate for a model in a collection to evaluate its recognition accuracy.
Compute the error rate for a model in a collection.
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Additional error rate computation parameters | |
| collId | Yes | Collection ID | |
| modelId | Yes | Model/HTR ID |
Changes observed during successful MCP inspections.
v2.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds no behavioral details beyond what annotations provide. It does not explain whether the computation is synchronous or asynchronous, whether it returns results directly, or any side effects. The openWorldHint=true suggests unknown behavior, but the description does not clarify.
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?
The description is a single sentence that is well-structured and concise. It conveys the essential purpose without excess words. However, it might be too brief, missing some important details. It earns points for efficiency but loses some for under-specification.
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?
The tool has no output schema, so the description should hint at what is returned or the nature of the output. It does not. Additionally, the compute action's behavior (synchronous/asynchronous, blocking, etc.) is not mentioned. Given the complexity and lack of output schema, the description is incomplete.
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?
The input schema covers all parameters with descriptions, so schema_description_coverage is 100%. The description does not add any additional meaning beyond what the schema provides. The 'body' parameter is vague, but the schema describes it as 'Additional error rate computation parameters'. A score of 3 is appropriate as the schema does the work, but the description adds no extra insight.
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?
The description clearly states 'Compute the error rate for a model in a collection', which is specific about the action and resources. However, it does not specify the type of error rate (e.g., CER, WER), which could be important for distinguishing from sibling tools like compute_wer. It does distinguish itself from compute_wer and compute_wer_tasas by using a more general term.
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?
The description provides no guidance on when to use this tool versus alternatives such as compute_wer or compute_sample. It does not mention prerequisites, context, or conditions for usage. The absence of any usage guidelines makes it hard for an agent to decide when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.