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get_article

Read-onlyIdempotent

Get the full amended text of one article of the EU AI Act, including lettered numbers such as "60a".

Input Schema

NameRequiredDescriptionDefault
numberYesArticle number, e.g. "6", "25", "60a"

Output Schema

NameRequiredDescriptionDefault
textYes
titleYes
eurlexNo
numberYes
permalinkYes
effective_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "effective_date": {
      +      "type": "string"
      +    },
      +    "eurlex": {
      +      "type": "string"
      +    },
      +    "number": {
      +      "type": "string"
      +    },
      +    "permalink": {
      +      "type": "string"
      +    },
      +    "text": {
      +      "type": "string"
      +    },
      +    "title": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "number",
      +    "title",
      +    "text",
      +    "permalink"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuine context: the returned text is the 'full amended' version rather than an excerpt, which tells the agent it gets the current consolidated article in its entirety.

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?

A single front-loaded sentence with zero waste; the scope constraint and the lettered-number caveat are both packed into one clause without padding.

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?

A one-parameter read tool with a full output schema and rich annotations needs little more than this. Nothing an agent requires to call it correctly is missing.

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 single 'number' parameter is already documented with examples. The mention of lettered numbers such as "60a" restates the schema example rather than adding new format or edge-case meaning, so baseline 3 applies.

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 (Get) and resource (full amended text of one article of the EU AI Act), and the resource name itself separates it from siblings like get_annex, get_recital and get_definition. An agent can tell exactly what it retrieves without opening the schema.

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?

Usage is implied: fetch a specific article by its number. There is no explicit guidance on when to prefer this over search_text or the other get_* siblings, and no prerequisites or exclusions are stated.

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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