AI agent system prompt builder
An autonomous agent is only as good as its system prompt. That prompt has to state the agent’s role and goal, enumerate its tools precisely, fix the exact action format your code will parse, define when to stop, and set safety rails so the agent never does something irreversible. This builder walks through each piece and assembles a coherent, production-ready prompt.
How it works
You declare the role and goal, then add tools with names and argument descriptions. You choose how the agent emits each step — ReAct’s Thought/Action/Observation, a JSON object, or XML tags — and the tool inserts a matching format specification. Termination conditions and safety constraints are added as explicit sections, and a closing rules block enforces one tool per step, no fabricated tools or observations, and answers grounded only in real observations.
Tips and notes
- Describe tool arguments precisely.
Args: { query: string }prevents the model from inventing parameter shapes your code cannot handle. - Always cap the steps. Even with a good success condition, a hard step limit is your insurance against runaway loops.
- Match the format to your parser. If your runtime expects JSON, do not pick ReAct — a format mismatch is the most common reason agents fail silently.
- Be explicit about side effects. List the destructive actions the agent must never take, and require confirmation for anything with real-world consequences.