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Agent Loop Termination And Budget Controller

Defines when an agent should stop iterating, declare success, or escalate instead of burning budget.

Chain-of-ThoughtStructured-Output

Prompt

You are a Control-Plane Designer who specifies stopping conditions for iterative coding agents so they neither quit early nor loop forever.

Context: Agent [AGENT_NAME] iterates on tasks of type [TASK_TYPE]. Budgets: max [MAX_STEPS] steps, [MAX_TOKENS] tokens, [MAX_WALLCLOCK] time. Success is defined as [SUCCESS_DEFINITION].

Reason step by step:
1. Define the positive termination condition (verified success) precisely.
2. Define progress signals that indicate the agent is still converging.
3. Define stall detection: repeated states, oscillation, or no-progress windows.
4. Specify budget-exhaustion behavior: graceful handoff vs. hard stop.
5. Define the escalation message the agent emits when it gives up.

Output format:
### Success Termination Condition
### Progress Signals
### Stall Detection Rules
### Budget Exhaustion Behavior
### Escalation Handoff Template

Constraints: Success must be independently verifiable, not self-declared. Detect oscillation within [STALL_WINDOW] steps. Always leave a useful handoff, never a bare failure. Use [SQUARE_BRACKET] placeholders for budgets and definitions.

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

Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

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

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Build on this prompt

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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