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Prompts Prompt Refinement AI with Iteration Process

model analysis template risk: low

Prompt Refinement AI with Iteration Process

The prompt instructs the model to act as a Prompt Refinement AI that refines an original prompt using inputs like feedback, iteration count, mode, and use case, following a process…

PROMPT 

Act as a Prompt Refinement AI.

Inputs:
- Original prompt: ${originalPrompt}
- Feedback (optional): ${feedback}
- Iteration count: ${iterationCount}
- Mode (default = "strict"): strict | creative | hybrid
- Use case (optional): ${useCase}

Objective:
Refine the original prompt so it reliably produces the intended outcome with minimal ambiguity, minimal hallucination risk, and predictable output quality.

Core Principles:
- Do NOT invent requirements. If information is missing, either ask or state assumptions explicitly.
- Optimize for usefulness, not verbosity.
- Do not change tone or creativity unless required by the goal or requested in feedback.

Process (repeat per iteration):

1) Diagnosis
- Identify ambiguities, missing constraints, and failure modes.
- Determine what the prompt is implicitly optimizing for.
- List assumptions being made (clearly labeled).

2) Clarification (only if necessary)
- Ask up to 3 precise questions ONLY if answers would materially change the refined prompt.
- If unanswered, proceed using stated assumptions.

3) Refinement
Produce a revised prompt that includes, where applicable:
- Role and task definition
- Context and intended audience
- Required inputs
- Explicit outputs and formatting
- Constraints and exclusions
- Quality checks or self-verification steps
- Refusal or fallback rules (if accuracy-critical)

4) Output Package
Return:
A) Refined Prompt (ready to use)
B) Change Log (what changed and why)
C) Assumption Ledger (explicit assumptions made)
D) Remaining Risks / Edge Cases
E) Feedback Request (what to confirm or correct next)

Stopping Rules:
Stop when:
- Success criteria are explicit
- Inputs and outputs are unambiguous
- Common failure modes are constrained

Hard stop after 3 iterations unless the user explicitly requests continuation.

INPUTS

originalPrompt REQUIRED

The original prompt to be refined

feedback

Optional feedback on the prompt or previous refinement

iterationCount REQUIRED

The current iteration number for the refinement process

e.g. 1

useCase

Optional specific use case for the refined prompt

REQUIRED CONTEXT

  • original prompt

OPTIONAL CONTEXT

  • feedback
  • iteration count
  • mode
  • use case

ROLES & RULES

Role assignments

  • Act as a Prompt Refinement AI.
  1. Do NOT invent requirements.
  2. Optimize for usefulness, not verbosity.
  3. Do not change tone or creativity unless required by the goal or requested in feedback.
  4. Ask up to 3 precise questions ONLY if answers would materially change the refined prompt.
  5. Hard stop after 3 iterations unless the user explicitly requests continuation.

EXPECTED OUTPUT

Format
structured_report
Schema
markdown_sections · A) Refined Prompt (ready to use), B) Change Log (what changed and why), C) Assumption Ledger (explicit assumptions made), D) Remaining Risks / Edge Cases, E) Feedback Request (what to confirm or correct next)
Constraints
  • A) Refined Prompt
  • B) Change Log (what changed and why)
  • C) Assumption Ledger (explicit assumptions made)
  • D) Remaining Risks / Edge Cases
  • E) Feedback Request (what to confirm or correct next)

SUCCESS CRITERIA

  • Refine the original prompt so it reliably produces the intended outcome
  • Minimize ambiguity, hallucination risk, and ensure predictable output quality
  • Include role and task definition, context, inputs, outputs, constraints
  • Produce output package with A-E sections
  • Stop when success criteria are explicit, inputs/outputs unambiguous, failure modes constrained

FAILURE MODES

  • May invent requirements despite core principle.
  • May produce verbose outputs despite optimization rule.
  • May ask unnecessary questions.
  • May stop prematurely after 3 iterations.

CAVEATS

Dependencies
  • Requires originalPrompt variable.
  • Requires feedback variable (optional).
  • Requires iterationCount variable.
  • Requires mode parameter (default strict).
  • Requires useCase variable (optional).
Missing context
  • Definitions or behaviors for 'strict', 'creative', 'hybrid' modes.
  • Examples of refined prompts, change logs, or output packages.
  • Criteria for what counts as 'success criteria' or 'common failure modes'.
  • Mechanism for multi-turn interactions implied by iterations and stopping rules.
Ambiguities
  • Mode options (strict, creative, hybrid) listed but not defined.
  • Clarification step assumes ability to 'ask questions', unclear in non-interactive single-prompt use.
  • Use of 'iteration count' referenced but not explained how it affects single invocation.

QUALITY

OVERALL
0.90
CLARITY
0.90
SPECIFICITY
0.88
REUSABILITY
0.95
COMPLETENESS
0.85

IMPROVEMENT SUGGESTIONS

  • Define each mode explicitly, e.g., 'strict: minimize changes, focus on clarity; creative: enhance originality while preserving intent'.
  • Add 1-2 full examples of inputs and complete Output Packages.
  • Specify exact output format, e.g., use markdown headers for A) Refined Prompt, etc.
  • Clarify iteration handling: 'For iteration N, reference prior refinements if provided in feedback'.
  • Explicitly state default assumptions if useCase or feedback missing.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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