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Ansvar-Systems

Slovak Data Protection MCP

sk_dp_search_decisions

Search Slovak data protection decisions by keyword, type, or topic. Retrieve references, fines, and cited GDPR articles from ÚOOÚ SR.

Instructions

Full-text search across ÚOOÚ SR decisions (rozhodnutia, pokuty, upozornenia). Returns matching decisions with reference, entity name, fine amount, and GDPR articles cited.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by decision type. Optional.
limitNoMaximum number of results to return. Defaults to 20.
queryYesSearch query (e.g., 'súhlas cookies', 'Slovak Telekom', 'porušenie ochrany')
topicNoFilter by topic ID (e.g., 'consent', 'cookies', 'transfers'). Optional.
Behavior3/5

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

No annotations are provided, so the description carries the burden of disclosing behavioral traits. It indicates full-text search and lists returned fields, which is useful context. However, it does not mention that the operation is read-only, how pagination behaves, or any limitations such as language or result ordering. It adds some behavioral details but lacks depth.

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 main purpose and a concise list of returned fields. Every word contributes to understanding, with no fluff or redundant information.

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

Completeness4/5

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

Given there is no output schema, the description sufficiently explains the return values (reference, entity name, fine amount, articles) and the search scope. Parameters are fully described in the schema. It doesn't mention error cases or pagination details, but the schema includes the limit default, so it is complete enough for a search tool.

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?

The input schema provides full descriptions for all 4 parameters (100% coverage), so the baseline is 3. The description does not add extra meaning about parameters; it only mentions output fields. Schema already explains query, type, limit, and topic, making additional description unnecessary.

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 'Full-text search across ÚOOÚ SR decisions' with specific decision types (rozhodnutia, pokuty, upozornenia) and enumerates returned fields (reference, entity name, fine amount, GDPR articles). It distinguishes this from siblings like sk_dp_get_decision (specific decision retrieval) and sk_dp_search_guidelines (guideline search).

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 usage for searching decisions but does not explicitly state when to use this tool over alternatives such as sk_dp_get_decision or sk_dp_search_guidelines. No exclusion criteria or alternative tool recommendations are provided, so usage context is implied rather than 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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