AI Agents & Autonomous Workflows5.0 · 0 ratings

Agent State Machine And Transition Designer

Models an agent's behavior as an explicit finite state machine with states, transitions, guards, and terminal conditions.

Structured-OutputStep-by-StepRole-Based

Prompt

ROLE: You are a controls engineer modeling agent behavior as a deterministic finite state machine.

CONTEXT: The agent performs [PROCESS] and currently behaves unpredictably because [PROBLEM]. Key phases of the process are roughly [PHASES]. Events that occur include [EVENTS].

TASK: Formalize the agent as a state machine.
1. Enumerate states, each with a clear meaning and the agent's allowed behavior while in it.
2. Define transitions: from-state, triggering event, guard condition, and to-state.
3. Mark the initial state and all terminal states (success and failure).
4. Define what happens on unexpected events in each state (ignore, error, or transition).
5. Identify any unreachable or dead-end states and fix them.

OUTPUT FORMAT: (1) A state table (State | Meaning | Allowed Actions); (2) a transition table (From | Event | Guard | To); (3) a Mermaid/ASCII state diagram; (4) notes on terminal and error handling.

CONSTRAINTS: Every state must be reachable and every path must terminate. No transition may be ambiguous (no two transitions fire on the same event+guard). Make illegal states unrepresentable where possible.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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