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Hermetics RGPD

by fr.hermetics
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GDPR obligations of a company

gdpr_obligations
Read-onlyIdempotent

Lists the GDPR obligations of a company established in an EU or EEA country from a few facts (size, website and cookies, e-mail marketing, sensitive data, video surveillance, AI...). Deterministic rules: each obligation comes with its legal basis and a suggested search_law query for the official text. A fact left out is treated as unknown, except processors, which are assumed.

Input Schema

NameRequiredDescriptionDefault
aiNoTrue if it develops or uses AI systems that interact with or make decisions about people.
cctvNoTrue if it uses video surveillance (CCTV).
countryYesCountry where the company is established (ISO code of an EU or EEA country, e.g. FR, DE, ES, IT).
websiteNoTrue if the company has a website or app.
employeesNoNumber of employees (0 if none).
processorsNoTrue if providers process personal data on its behalf (hosting, SaaS, payroll, CRM). Assumed true if omitted.
large_scaleNoTrue if the processing concerns a large number of people (large scale).
public_sectorNoTrue if the organisation is a public authority or public body.
email_marketingNoTrue if the company sends marketing e-mails or SMS to individuals.
vulnerable_peopleNoTrue if it processes data of vulnerable people (children, patients, elderly people).
automated_decisionsNoTrue if it takes automated decisions with legal or similarly significant effects on people.
evaluation_or_scoringNoTrue if it evaluates or scores people (credit scoring, profiling, performance rating).
non_essential_cookiesNoTrue if the website or app uses non-essential cookies or trackers (analytics, advertising, social media pixels).
special_category_dataNoTrue if it processes special category data (health, biometrics, genetic data, religion, union membership, sex life or orientation, ethnic origin, political opinions).
systematic_monitoringNoTrue if it systematically monitors people (online behaviour tracking, geolocation, profiling for advertising, CCTV of public areas).
transfers_outside_eeaNoTrue if personal data is sent to providers or entities outside the EEA (e.g. US SaaS).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world). The description adds real behavioral context beyond them: deterministic rules, the fact that each obligation includes a legal basis and a suggested query, and the default-handling rule for omitted facts. It does not describe output volume or edge-case failure modes, keeping it at 4.

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?

Three tight sentences: purpose first, then the deterministic/output behavior, then the default-handling rule. No filler and each sentence carries decision-relevant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 16 parameters, no output schema, and a non-trivial domain, the description supplies what the schema cannot: the return content (legal basis + suggested search_law query) and the omission-handling default. An agent has everything needed to call and interpret this tool.

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 coverage is 100%, so the baseline is 3, but the description adds the general default semantics ('a fact left out is treated as unknown, except processors, which are assumed') that the schema only states for the processors parameter. That generalization helps the agent decide how much to supply, though it does not add per-parameter detail.

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?

States a specific verb ('Lists') and resource (GDPR obligations) with clear scope (company established in EU/EEA) and the inputs it reasons from. It is easily distinguished from siblings like search_law, which it explicitly hands off to for official text.

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

Usage Guidelines4/5

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

It gives clear context for use (deriving obligations from a few facts) and routes the agent to search_law for the official legal text, which is an explicit alternative. It stops short of stating when NOT to use it or prerequisites, but the routing guidance is genuinely useful.

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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