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Leviai-ai

AI Compliance Calendar MCP Server

by Leviai-ai

jurisdiction_compare

Compare AI regulations across jurisdictions to analyze differences in approach, requirements, timelines, and penalties. Use it to identify compliance gaps and align policies.

Instructions

Compare AI regulations across multiple jurisdictions. Analyze differences in approach, requirements, timelines, and penalties.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focus_areaNoSpecific area to focus on: privacy, safety, transparency, penalties, timelines
jurisdictionsYesJurisdictions to compare (e.g., ['EU', 'US', 'UK'])

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, but it discloses nothing about data freshness, whether the comparison is generated or retrieved, latency, or any access constraints. It only restates the analytical dimensions already implied by the focus_area field.

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?

Two short sentences, front-loaded with the core verb and resource, then the analysis scope. No filler or redundancy.

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

Completeness3/5

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

For a two-parameter read tool with a fully documented schema this is minimally adequate, but with no annotations and no output schema the description should say something about what a comparison returns (structured table, narrative, per-dimension breakdown) and any jurisdiction count limits.

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 coverage is 100%, so both parameters are already documented with examples and allowed focus values. The description lists comparison dimensions (approach, requirements, timelines, penalties) that loosely echo the focus_area options but add no syntax, format, or defaulting information beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Compare') and resource ('AI regulations across multiple jurisdictions'), plus the dimensions of comparison. This is clearly distinguishable from get_regulations and regulation_summary by intent, though the description never names an alternative to reinforce the distinction.

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

Usage Guidelines2/5

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

No explicit guidance on when to choose this over regulation_summary (single-jurisdiction summary) or get_regulations (fetch). Usage is only weakly implied by the cross-jurisdiction framing, and there are no prerequisites or exclusions stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.