AI Agent System Prompt Generator
Build a production-ready system prompt for any AI agent. Pick a role, tools, output format, guardrails, and tone, then copy the result.
Agent settings
System prompt
Generated prompt
What makes a strong system prompt
- • One sentence role: who the agent is and who it serves.
- • One sentence goal: the single outcome it optimizes for.
- • Tool list: only tools the agent actually has access to.
- • Output spec: exact structure the downstream system expects.
- • Guardrails: hard refusal rules and escalation triggers.
- • Examples: at least one positive and one refusal example.
Before going live
- • Test with adversarial prompts and edge cases.
- • Redact any internal URLs or credentials.
- • Add version control and A/B test changes.
- • Log refusals and unexpected outputs.
- • Review for compliance with your data policy.
- • Pair with an evaluation benchmark from the selector.
Build, test, and deploy the agent
Once you have a system prompt, estimate cost, pick a benchmark, and stack the components.
Frequently asked questions
What should a good system prompt include?
A clear role, goal, allowed tools, output format, guardrails, workflow steps, tone rules, examples, and escalation instructions.
How do guardrails help?
Guardrails prevent the agent from leaking PII, giving medical/legal advice, going off-topic, or hallucinating. They define what the agent must refuse or escalate.
Can I use this prompt with any LLM?
Yes. The generated prompt is plain text. You can paste it into OpenAI, Anthropic, Google, Groq, or any local model that supports system prompts.
Why specify output format?
Structured output (JSON, bullets, steps) makes the agent easier to parse, evaluate, and integrate into downstream systems.
Should I include examples?
Yes. One good input/output example beats a long description. Include edge cases and refusal examples for safety-critical agents.