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eu_mdr_compliance

Determine EU MDR classification and conformity assessment route for AI medical devices based on device details and intended purpose.

Instructions

Assess EU Medical Device Regulation (MDR 2017/745) compliance for AI-based medical devices. Determines MDR classification, conformity assessment route, and regulatory requirements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
risk_classYesEstimated risk class (Class I, IIa, IIb, III) or 'unknown' for classification assistance
system_nameYesName of the AI medical device
intended_purposeYesIntended purpose per MDR Article 2(12)
device_descriptionYesDescription of the device including AI/ML components
Behavior2/5

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

With no annotations, the description carries full burden for behavioral traits. It describes what the tool assesses but does not disclose output format, prerequisites, limitations, or any side effects. For a tool that determines regulatory requirements, missing details like 'generates a compliance report' or 'requires clinical evidence' reduce transparency.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the tool's purpose, and contains no filler. Every sentence adds value.

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?

The description explains the tool's function but does not detail the output or any prerequisites. With no output schema, the agent cannot anticipate what the tool returns (e.g., classification text, structured report). Additional information about the response would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with each parameter described. The tool description adds meaning by referencing MDR Article 2(12) for intended_purpose and specifying 'including AI/ML components' for device_description, enriching the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool assesses EU MDR 2017/745 compliance for AI-based medical devices, specifying it determines classification, conformity assessment route, and regulatory requirements. This clearly distinguishes it from sibling tools focusing on clinical safety, FDA, and HIPAA.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for EU MDR compliance but does not explicitly state when to use this tool versus the sibling tools (e.g., fda_ai_assessment for US FDA). The sibling names are provided in context, but the description lacks explicit usage exclusions or alternatives.

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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