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Legion33shadow

legion-ai-intelligence

get_ai_regulations

Search AI regulations and policy documents by keyword to find relevant compliance information.

Instructions

Search AI regulations and policy documents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
searchNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
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 and discloses almost nothing: not whether the call is read-only, what an empty search returns, how results are ordered, or how `limit` interacts with matching. It relies entirely on the reader inferring safe read behavior from the name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single short sentence is front-loaded and wastes no words, which is structurally good. However, the brevity here is under-specification rather than effective conciseness, so it does not earn a 4.

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

Completeness2/5

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

An output schema exists, so return values need not be explained, but with zero annotation coverage, zero parameter documentation, and no usage framing, the definition leaves the agent guessing on nearly every invocation detail for a two-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so neither `limit` nor `search` is explained in the schema. The description adds no meaning either — it only loosely implies that a search term exists, without stating matching semantics, default behavior for an empty string, or what `limit` bounds.

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?

The description pairs a specific verb ("Search") with a specific resource ("AI regulations and policy documents"), so an agent knows exactly what it retrieves. No sibling tool covers regulations or policy, so the lack of explicit sibling differentiation is not a real gap here.

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?

There is no statement of when to use this tool versus alternatives, no mention of prerequisites, and no condition under which it should be avoided. The only usage signal is the implied one carried by the word "Search," which is not enough for a 3.

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