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Sovereign AI Act MCP

review_feature

EU AI Act CO-PILOT review for builders: pass a feature, spec or behaviour you are about to ship and get a ship/caution/stop signal (OK / TRANSPARENCY / REVIEW REQUIRED / STOP), the binding Articles, the obligations that apply, red flags and concrete next steps — grounded verbatim in Regulation (EU) 2024/1689. Use proactively while designing or coding an AI feature, before it ships.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesThe AI feature, spec or behaviour you are about to build/ship.
languageNoen

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and largely delivers: it discloses that the tool takes a feature description and returns a signal, binding Articles, obligations, red flags, and next steps, grounded verbatim in the regulation. It does not explicitly mention side effects, authentication, or rate limits, but as a review tool these are not material gaps.

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 a single dense sentence with no filler, front-loading the purpose and then packing in the output contract and usage timing. It could be split for readability, but every clause contributes value.

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?

Despite having no output schema or annotations, the description explains the outcome space, the regulatory grounding, and when to use the tool. The main gaps are the undocumented language parameter and lack of response-format details, but the core call contract is clear enough for an agent to proceed.

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 parameter is echoed with examples ('feature, spec or behaviour'), but the input schema already describes it. The language parameter is entirely undocumented in both the schema and the description, so the description only partially compensates for the 50% schema description coverage.

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 and resource: 'review a feature, spec or behaviour you are about to ship'. It enumerates the concrete verdict types (OK / TRANSPARENCY / REVIEW REQUIRED / STOP) and the outputs (binding Articles, obligations, red flags, next steps), which clearly distinguishes it from sibling lookup/search/classification tools.

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?

Provides an explicit usage context: 'Use proactively while designing or coding an AI feature, before it ships.' It does not explicitly name siblings or say when not to use it, so it falls short of full routing guidance, but the timing and intent are clear.

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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