Support Ticket Triage MCP

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get_queue_metrics

Read-onlyIdempotent

Calculates current support ticket queue metrics, including SLA status, recommendations, and savings, to inform triage decisions.

Instructions

Calculate current queue, SLA, recommendation, and savings metrics.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_queue_metrics"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`generatedAt`	Yes
`openTickets`	Yes
`rejectionRate`	Yes
`ticketsByTeam`	Yes
`acceptanceRate`	Yes
`escalationCounts`	Yes
`slaAtRiskTickets`	Yes
`untriagedTickets`	Yes
`averageConfidence`	Yes
`ticketsByCategory`	Yes
`ticketsByPriority`	Yes
`slaBreachedTickets`	Yes
`estimatedMinutesSaved`	Yes
`pendingRecommendations`	Yes
`approvedRecommendations`	Yes
`rejectedRecommendations`	Yes
`submittedRecommendations`	Yes
`minutesPerAcceptedRecommendation`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 11, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the metric categories and the 'current' qualifier, providing useful context about the tool's scope without contradicting 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?

The description is a single sentence with no filler, stating exactly what the tool calculates. It is appropriately sized for a zero-parameter tool.

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?

Given the zero-parameter input, comprehensive annotations, and presence of an output schema, the description sufficiently explains the tool's purpose and scope. It names all metric types returned, making it complete without over-explaining.

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

Parameters4/5

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

The tool has zero parameters, so the baseline score of 4 applies. The description does not need to explain any parameters.

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?

The description uses the specific verb 'Calculate' and identifies four distinct metric categories (queue, SLA, recommendation, savings). This clearly differentiates it from sibling tools that focus on individual tickets, audit events, or recommendation approvals.

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 usage guidance or alternative tools are mentioned. The description implies it's the metrics aggregation tool, but doesn't state when to prefer it over list_tickets or get_ticket, so usage is only implied.

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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