x402-eu-data-check
Eu Data Check: GDPR, EU AI Act, DMA, DSA quick assessment.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | Text to process | |
| input | No | Input to process |
Eu Data Check: GDPR, EU AI Act, DMA, DSA quick assessment.
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | Text to process | |
| input | No | Input to process |
Changes observed during successful MCP inspections.
Input schema / properties / textAdded value: +{
+ "description": "Text to process",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it does not state what the assessment returns, whether it is advisory or authoritative, what inputs are required, or any limits. 'Quick assessment' conveys speed but nothing about output or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
It is a single short sentence with no filler, which is good, but it is essentially a label duplicating the tool name rather than front-loading actionable content. Brevity here reflects under-specification rather than efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and two confusingly similar parameters, the definition is too thin for an agent to call the tool correctly. Nothing explains the expected input format or what the assessment produces.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema description coverage is nominally 100%, both parameter descriptions are tautological ('Text to process' / 'Input to process'), leaving it unclear which field the agent should populate and whether they differ. The description adds no clarification, so it fails to resolve the text-vs-input ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Naming the regulations (GDPR, EU AI Act, DMA, DSA) and 'quick assessment' gives some sense of the resource and operation, but the verb is vague — it does not say whether it classifies text, flags violations, or produces a report. Nothing distinguishes it from EU-related siblings such as x402-eu-brief or x402-eu-indices beyond the regulation list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool, when not to, or what alternative to pick instead. With hundreds of siblings, the absence of any routing guidance leaves the agent to guess.
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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