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KevinRabun

io.github.KevinRabun/GDPRShiftLeftMCP

by KevinRabun

assess_controller_processor_role

Analyze a service description to determine GDPR role as controller, processor, or joint controller, clarifying data protection obligations.

Instructions

Assess whether a service/system acts as data controller, processor, joint controller, or has a mixed role under GDPR.

Analyzes the service description against GDPR definitions and EDPB guidance to determine the likely role and associated obligations.

Args: service_description: Description of the service, data flows, business relationships, and processing activities

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
service_descriptionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool 'assesses' and 'analyzes', implying it is read-only, but it does not explicitly confirm non-destructive behavior, required permissions, or potential side effects. The description lacks transparency about what happens to the input or system state.

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 relatively concise: a clear one-sentence summary followed by a brief explanation and the parameter description. The Args section adds value without being overly verbose. It loses a point for minor redundancy (the second sentence partially restates the first) but is generally efficient.

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 tool has a single parameter, an output schema (not shown), but no sibling or annotation context. The description covers the input well but does not mention what the tool returns (the role classification). Since an output schema exists, the burden is lower, but the description would benefit from a brief note on output format.

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?

The input schema has zero description coverage for the single parameter, so the description must compensate. It does so by detailing that 'service_description' should include the service, data flows, business relationships, and processing activities. This adds significant meaning beyond the schema's simple title and type.

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's purpose: to assess whether a service/system acts as a data controller, processor, joint controller, or mixed role under GDPR. It uses a specific verb (assess) and a concrete resource (GDPR role), and the role is distinct from sibling tools like analyze_data_flow or get_role_obligations.

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 explains that the tool analyzes service descriptions against GDPR definitions and EDPB guidance, which implies its usage context. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusion criteria or prerequisites. The guidance is adequate but not explicit.

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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