GIA MCP Server

classify_decision

Read-onlyIdempotent

Classify AI agent decisions using the MAI Framework to identify whether they require mandatory, advisory, or informational gates, with confidence and rationale.

Instructions

Classify an AI agent decision using the MAI Framework (Mandatory/Advisory/Informational). Returns classification level, confidence score, gate requirements, and rationale.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "decision": "<decision>",
      "domain": "<domain>"
    },
    "name": "classify_decision"
  }
}

Input Schema

Name	Required	Description
`decision`	Yes	Description of the decision to classify
`domain`	Yes	Domain context
`agent_name`	No	Name of the agent making the decision
`is_client_facing`	No	Whether output is client-facing
`has_financial_impact`	No	Whether action has financial impact
`has_legal_impact`	No	Whether action involves legal assertions

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.3.6May 13, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds value by specifying return fields (classification level, confidence, gates, rationale) and mentions MAI framework, which is not in annotations.

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?

Single sentence that efficiently conveys purpose, framework, and output. No redundant or filler content.

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?

No output schema exists, but description outlines return values. Covers key aspects for an AI agent to decide invocation, though could detail what 'gate requirements' means.

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 has 100% description coverage for all 6 parameters. The description does not add additional meaning beyond what the schema already provides; baseline score 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?

Clear verb 'classify' with specific resource 'AI agent decision using the MAI Framework'. Distinct from siblings by focusing on classification into Mandatory/Advisory/Informational levels.

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?

No explicit guidance on when to use versus alternatives like assess_risk_tier or evaluate_threshold. Implied by purpose but no contextual differentiation.

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

Deploy Server