코딩
프롬프트 최적화 도구
⚙️ PromptForge
주어진 프롬프트를 진단하고 범위를 정의한 뒤, 모호성을 제거한 정밀한 버전으로 다시 작성합니다. 간결한 버전과 상세한 버전, 실패 시나리오와 엣지 케이스를 포함한 스트레스 테스트 결과를 제공합니다.
- 테스트 모델:
- GPT-4o
- 효과 점수:
- 95/100
- 프롬프트 아카이브
한국어 버전
You are a senior prompt engineer, system designer, and critical evaluator.
Your task is to rigorously analyze, optimize, and validate the given prompt for maximum clarity, determinism, robustness, and consistent high-quality output.
You must follow every step strictly. Do not skip, merge, or reorder steps.
1. Diagnostic Analysis
* Strengths
* Weaknesses (ambiguities, vagueness, missing constraints)
* Hidden assumptions
* Misinterpretation risks
* Unstated dependencies (context, knowledge, format expectations)
2. Scope Definition
* Define what is explicitly in-scope
* Define what is out-of-scope
* Identify boundary conditions
3. Precision Rewrite
* Rewrite the prompt to eliminate all ambiguity
* Add explicit constraints, structure, and instructions
* Define expected output format clearly
* Preserve the original goal exactly (do not alter intent)
4. Alternative Variants
* Version A: Minimal / concise (short, strict, low ambiguity)
* Version B: Detailed / structured (step-by-step, high control)
5. Stress Test
* List realistic failure scenarios
* Provide concrete examples of poor or incorrect outputs
* Explain root causes of each failure
* Identify edge cases and boundary conditions
6. Final Optimized Prompt
* Provide the single best version
* Balance clarity, control, and flexibility
* Ensure reusability across similar tasks
* Ensure it is self-contained (no missing context required)
7. Acceptance Criteria
The final prompt MUST:
* Be explicit and unambiguous
* Clearly define output format and structure
* Minimize interpretation variance
* Include all necessary constraints (tone, scope, format, limits)
* Handle edge cases or explicitly bound them
* Be reusable and self-contained
8. Evaluation Rubric (Score 1–5 for each with brief justification)
* Clarity
* Specificity
* Determinism
* Robustness (edge cases)
* Output Control
9. Assumption Policy
* Do not make unstated assumptions
* If critical information is missing, explicitly state what is missing
* Either proceed with clearly stated assumptions OR request clarification
10. Output Constraints
* Define expected output length (if applicable)
* Define format strictly (e.g., bullet points, JSON, paragraph)
* Avoid unnecessary verbosity
11. Default Behaviors
* If multiple valid interpretations exist, choose the most conservative and explicit one
* If uncertainty remains, state assumptions before proceeding
* Prefer clarity over brevity when trade-offs occur
12. Self-Check and Refinement
* Verify the final prompt meets ALL acceptance criteria
* Identify any remaining ambiguity or weakness
* If any issue exists, refine the final prompt once more
* Present the corrected final version
13. Output Format (STRICT)
Use exactly these section headers in this order:
* Diagnostic Analysis
* Scope Definition
* Precision Rewrite
* Alternative Variants
* Stress Test
* Final Optimized Prompt
* Acceptance Criteria
* Evaluation Rubric
* Assumption Policy
* Output Constraints
* Default Behaviors
* Self-Check and Refinement
Rules:
* Be critical, precise, and direct
* Avoid generic or vague advice
* Make all improvements concrete and actionable
* Do not change the core intent of the prompt
* Do not omit constraints when they improve reliability
* Do not produce outputs outside the defined format
Prompt to evaluate:
${paste_prompt_here}
Goal:
${describe_the_exact_desired_output}
(Optional) Example of ideal output:
${provide_if_available}값을 채워 바로 실행
이 프롬프트에는 채울 곳이 3군데 있습니다. 값을 넣으면 완성된 프롬프트를 만들어 드립니다.
3군데 남음
완성된 프롬프트
You are a senior prompt engineer, system designer, and critical evaluator.
Your task is to rigorously analyze, optimize, and validate the given prompt for maximum clarity, determinism, robustness, and consistent high-quality output.
You must follow every step strictly. Do not skip, merge, or reorder steps.
1. Diagnostic Analysis
* Strengths
* Weaknesses (ambiguities, vagueness, missing constraints)
* Hidden assumptions
* Misinterpretation risks
* Unstated dependencies (context, knowledge, format expectations)
2. Scope Definition
* Define what is explicitly in-scope
* Define what is out-of-scope
* Identify boundary conditions
3. Precision Rewrite
* Rewrite the prompt to eliminate all ambiguity
* Add explicit constraints, structure, and instructions
* Define expected output format clearly
* Preserve the original goal exactly (do not alter intent)
4. Alternative Variants
* Version A: Minimal / concise (short, strict, low ambiguity)
* Version B: Detailed / structured (step-by-step, high control)
5. Stress Test
* List realistic failure scenarios
* Provide concrete examples of poor or incorrect outputs
* Explain root causes of each failure
* Identify edge cases and boundary conditions
6. Final Optimized Prompt
* Provide the single best version
* Balance clarity, control, and flexibility
* Ensure reusability across similar tasks
* Ensure it is self-contained (no missing context required)
7. Acceptance Criteria
The final prompt MUST:
* Be explicit and unambiguous
* Clearly define output format and structure
* Minimize interpretation variance
* Include all necessary constraints (tone, scope, format, limits)
* Handle edge cases or explicitly bound them
* Be reusable and self-contained
8. Evaluation Rubric (Score 1–5 for each with brief justification)
* Clarity
* Specificity
* Determinism
* Robustness (edge cases)
* Output Control
9. Assumption Policy
* Do not make unstated assumptions
* If critical information is missing, explicitly state what is missing
* Either proceed with clearly stated assumptions OR request clarification
10. Output Constraints
* Define expected output length (if applicable)
* Define format strictly (e.g., bullet points, JSON, paragraph)
* Avoid unnecessary verbosity
11. Default Behaviors
* If multiple valid interpretations exist, choose the most conservative and explicit one
* If uncertainty remains, state assumptions before proceeding
* Prefer clarity over brevity when trade-offs occur
12. Self-Check and Refinement
* Verify the final prompt meets ALL acceptance criteria
* Identify any remaining ambiguity or weakness
* If any issue exists, refine the final prompt once more
* Present the corrected final version
13. Output Format (STRICT)
Use exactly these section headers in this order:
* Diagnostic Analysis
* Scope Definition
* Precision Rewrite
* Alternative Variants
* Stress Test
* Final Optimized Prompt
* Acceptance Criteria
* Evaluation Rubric
* Assumption Policy
* Output Constraints
* Default Behaviors
* Self-Check and Refinement
Rules:
* Be critical, precise, and direct
* Avoid generic or vague advice
* Make all improvements concrete and actionable
* Do not change the core intent of the prompt
* Do not omit constraints when they improve reliability
* Do not produce outputs outside the defined format
Prompt to evaluate:
${paste_prompt_here}
Goal:
${describe_the_exact_desired_output}
(Optional) Example of ideal output:
${provide_if_available}- ChatGPT에서 열기 (새 탭에서 열림)
- Claude에서 열기 (새 탭에서 열림)
- Gemini에서 열기 (새 탭에서 열림)
Gemini는 링크로 프롬프트를 전달할 수 없어, 먼저 복사해 주세요.
- Perplexity에서 열기 (새 탭에서 열림)
새 탭이 열리고 프롬프트가 미리 입력됩니다. 서비스에 로그인되어 있어야 할 수 있습니다.
이 프롬프트 사용법
- 대괄호로 표시된 부분을 여러분의 내용으로 바꿔서 입력하세요.
- 모델에 따라 결과가 달라집니다. 원하는 답이 아니면 다른 모델을 쓰거나 구체적인 예시를 하나 덧붙이세요.
- 프롬프트는 한 번에 하나의 메시지로 보내세요. 여러 번에 나누면 지시가 약해집니다.