Describe the job you want an AI agent to handle and get a system prompt in five labelled blocks: persona, objective, process, restrictions, and what to do when it is unsure. Keeping identity and hard rules apart is the point, so you can tighten a restriction without rewriting the character. Paste the result into a ChatGPT Custom GPT, a Claude Project, or any agent platform.
Most system prompts fail the same way: they describe a mood instead of a job, and their rules cannot be checked.
Because they change for different reasons. Persona is who the agent is and how it speaks; restrictions are the hard limits it can be held to. When they are mixed into one paragraph, tightening a rule means rewriting the character, and it gets hard to tell whether the agent broke a rule or was just being itself. Split, you can edit either one alone.
PERSONA (who it is and how it speaks), OBJECTIVE (the single outcome it owns), PROCESS (the ordered steps it takes), RESTRICTIONS (hard limits, each one checkable from a transcript), and WHEN UNSURE (its exact fallback behaviour).
It is held to roughly 200-320 words on purpose. Long system prompts dilute attention and bury the rules that matter, and every line that would leave the agent behaving identically if deleted is a line making the important ones harder to follow.
No. It writes the system prompt that defines how an agent should behave. You paste that into a platform such as a ChatGPT Custom GPT, a Claude Project, or your own code to actually run it.
No. Describe the task in plain English and you get instructions you can paste into a no-code agent platform. If you want runnable code instead, use the Prompt-to-Agent Scaffold.
Those mark real details the prompt needs that you did not supply, such as a product name or an escalation contact. They are left blank rather than invented so nothing false ends up in your agent's instructions.