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BenjaminJ

enterprise-mcp-gateway

listSupportTickets

Retrieve open and resolved support tickets by customer ID or urgency to check active issues, SLA status, and service incidents.

Instructions

Query customer support tickets - Queries open and resolved support tickets across the organization. Can be filtered by customerId or ticket urgency priority. Use this tool to check active issues, SLA status, or service incidents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
priorityNoFilter tickets by urgency level ('low', 'normal', 'high', 'urgent').
customerIdNoOptional filter to retrieve support tickets for a specific customer ID (e.g., 'cust-001').
Behavior3/5

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

With no annotations provided, the description carries the full burden. It correctly signals read-only behavior via 'Query', states that both open and resolved tickets are included, and notes the org-wide scope. However, it does not mention response shape, pagination, default behavior when no filters are supplied, or other operational caveats.

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 compact and front-loaded: purpose first, then scope, then filters and typical use cases. There is no fluff, and the structure makes it easy to parse quickly.

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?

For a simple read-only listing tool with two optional parameters and no output schema, the description plus schema provides enough context for correct invocation. The main gaps—return format and behavior without filters—are not blocking for this complexity level.

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?

Both parameters are fully documented in the schema with descriptions and examples (100% coverage), so the description adds little semantic value beyond restating that filters exist. It does not clarify whether filters combine or what the default behavior is when omitted.

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 a specific verb ('Query') and a specific resource ('customer support tickets'), then adds scope ('open and resolved across the organization'). This clearly distinguishes it from siblings like createSupportTicket, getCustomerDetails, and getBillingHistory, which cover creation or other customer/billing resources.

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?

It tells the agent exactly when to reach for the tool ('Use this tool to check active issues, SLA status, or service incidents') and the available filters (customerId, priority). It does not explicitly name alternatives or state when not to use it, but the use cases are concrete enough.

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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