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clinical_ai_safety

Assess clinical AI safety covering bias, validation, human oversight, and EU AI Act obligations with CASA tier recommendation.

Instructions

Comprehensive clinical AI safety assessment covering bias, validation, human oversight, and EU AI Act obligations for healthcare AI systems. Provides CASA tier recommendation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
system_nameYesName of the clinical AI system
clinical_domainYesClinical domain (e.g., radiology, pathology, cardiology, oncology, drug prescribing)
decision_autonomyYesLevel of AI decision autonomy (e.g., advisory, decision support, autonomous, triage)
patient_populationYesTarget patient population (e.g., adult, pediatric, geriatric, specific demographics)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states what the tool covers but does not disclose behavioral traits such as whether it is read-only, any authorization needs, or side effects. For a computation tool, it is likely non-destructive, but this is not explicitly stated.

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 focused sentence that front-loads the purpose and scope. It is concise without wasted words, though it could be slightly more structured.

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 and 4 required parameters, the description is vague about what is returned ('CASA tier recommendation') and does not explain the output format or provide context on CASA tiers. This leaves the agent uncertain about what to expect.

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?

Schema description coverage is 100%, so the schema already documents all four parameters. The description adds no additional semantics for the parameters; it only says the assessment covers certain topics which are not parameters.

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 it performs a clinical AI safety assessment covering bias, validation, human oversight, and EU AI Act, and outputs a CASA tier recommendation. However, it does not explicitly differentiate from sibling tools (eu_mdr_compliance, fda_ai_assessment, hipaa_ai_assessment), which would help an agent choose.

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 this tool is for comprehensive safety assessment including EU AI Act, but does not specify when to use it versus sibling tools that cover specific regulations. No exclusions or alternatives are given.

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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