IntermediateAgent DesignFree prompt

Write a Robust System Prompt for a Customer-Facing Agent

Generate a production-grade system prompt with role, tone, tool-use rules, refusal policy, and escalation path for an agent that talks to real users.

Get a system prompt that holds up under adversarial users, ambiguous requests, and edge cases instead of one that only works in the happy path.

system promptcustomer supporttonerefusal policyescalation

At a glance

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Prompt objective

Get a system prompt that holds up under adversarial users, ambiguous requests, and edge cases instead of one that only works in the happy path.

Real use case

A SaaS support team is moving from canned macros to a Claude- or GPT-powered assistant and needs a system prompt that stays on-brand, never invents policy, and escalates billing disputes to a human.

Customize these fields first

PRODUCT NAME AND ONE-LINE DESCRIPTIONE.G. WARM, DIRECT, NO HYPEALLOWED ACTIONSPROHIBITED ACTIONSTOOLSWHEN AND HOW TO HAND OFF TO A HUMAN

Replace the placeholders with your own context before you run the prompt. That usually improves the first output more than adding more instructions later.

Prompt

Act as an AI agent prompt engineer. Write a complete production system prompt for a customer-facing agent.

Product: [PRODUCT NAME AND ONE-LINE DESCRIPTION]
Brand voice: [E.G. WARM, DIRECT, NO HYPE]
What it CAN do: [ALLOWED ACTIONS]
What it must NEVER do: [PROHIBITED ACTIONS]
Tools it can call: [TOOLS]
Escalation path: [WHEN AND HOW TO HAND OFF TO A HUMAN]

The system prompt you write must include, clearly labeled:
- Role and primary objective
- Tone and formatting rules (length, when to use lists, when to ask a clarifying question)
- Tool-use policy: when to call each tool, and the rule "never claim you did something you did not actually do via a tool"
- Grounding rule: only state policy/pricing/facts that come from a tool or provided context; otherwise say you will check
- Refusal and safety policy with example phrasings
- Escalation triggers and the exact handoff message
- 3 few-shot examples (user message → ideal agent response) covering one happy path, one ambiguous request, one out-of-scope request

Output only the final system prompt, ready to paste.

Open directly in an AI — the text is pre-filled:

How to use this prompt

  1. 1Replace the key placeholders first: PRODUCT NAME AND ONE-LINE DESCRIPTION, E.G. WARM, DIRECT, NO HYPE, ALLOWED ACTIONS, PROHIBITED ACTIONS.
  2. 2Replace any bracketed placeholders like [this] with your own context.
  3. 3Add extra background information when you want more tailored results.
  4. 4Combine multiple prompts in one conversation when you need a richer output.
  5. 5Save your best-performing prompts so they are easy to reuse later.

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