Customer Support Agent Workflow

Define a bounded support-agent decision loop with tool use and human escalation.

Models: ChatGPT, Claude
Level: Advanced
Version: v0.9

What this prompt does

Define a bounded support-agent decision loop with tool use and human escalation.

Best for

JSON containing intent, facts, missing information, planned tool calls, policy checks, response, escalation status, and audit note.

Prompt variables

[PRODUCT_POLICY][TOOLS][ESCALATION_RULES][CUSTOMER_MESSAGE]

System Prompt

You design safe support workflows. Policies and tool permissions are authoritative; never promise an action that a tool did not confirm.

User Prompt

OBJECTIVE:
Handle [CUSTOMER_MESSAGE] using [PRODUCT_POLICY], available tools [TOOLS], and [ESCALATION_RULES].

INPUTS:
PRODUCT_POLICY: [PRODUCT_POLICY]
TOOLS: [TOOLS]
ESCALATION_RULES: [ESCALATION_RULES]
CUSTOMER_MESSAGE: [CUSTOMER_MESSAGE]

OUTPUT CONTRACT:
JSON containing intent, facts, missing information, planned tool calls, policy checks, response, escalation status, and audit note.

How to use

Replace every variable with specific, non-sensitive information. Remove irrelevant sections and add one representative example when tone or classification matters.

Why it works

The blueprint separates authority, task context, evidence limits, and the output contract so requirements can be checked independently.

Model compatibility

ChatGPTuntestedEditorial compatibility hypothesis; cross-model test record pending.

ClaudeuntestedEditorial compatibility hypothesis; cross-model test record pending.

Example input

PRODUCT_POLICY: [PRODUCT_POLICY]
TOOLS: [TOOLS]
ESCALATION_RULES: [ESCALATION_RULES]
CUSTOMER_MESSAGE: [CUSTOMER_MESSAGE]

Example output

A structured deliverable following the listed output contract, with assumptions and missing evidence clearly marked.

How to customize

Replace every variable with specific, non-sensitive information. Remove irrelevant sections and add one representative example when tone or classification matters.