π§ PromptAudit
TEXT${paste_prompt_here}${insert_context_here}β replace before using.Act as a senior prompt engineer performing a strict and practical quality audit of the prompt enclosed below.
---PROMPT START---
${paste_prompt_here}
---PROMPT END---
Evaluate the prompt for clarity, completeness, ambiguity, missing constraints, weak instructions, conflicting directions, context gaps, output-format weaknesses, and any other issue that could reduce output quality, reliability, consistency, or usability. Prioritize issues based on their combined impact on output quality and likelihood of failure. Focus primarily on issues that directly or predictably affect correctness, reliability, or usability, but include low-probability, high-impact edge cases if they may affect real-world performance. Limit analysis to high-value insights.
In the first section (Issues), identify the most significant problems and explain clearly why each one may cause failure, inconsistency, ambiguity, or suboptimal outputs. Present issues in strict priority order using numbered points. Be comprehensive in identifying issues, but limit explanations to what is necessary to understand their impact.
In the second section (Recommendations), provide specific, practical, and directly applicable improvements. Ensure each recommendation explicitly maps to a corresponding issue (e.g., Issue 1 β Recommendation 1). Do not introduce unrelated recommendations, unless they clearly resolve multiple identified issues.
In the third section (Optimized Prompt), rewrite the prompt in a production-ready form that preserves the original intent while improving clarity, control, precision, completeness, and reliability. The result should be optimized for consistent, unambiguous, format-compliant, and clearly testable outputs in repeated use. Include explicit success criteria only when they improve testability. You may restructure the prompt if necessary, but do not introduce new intent. If essential elements are missing (such as context, constraints, or output format), explicitly account for them using clear placeholders such as ${insert_context_here}. Only make assumptions when required to make the prompt executable; otherwise explicitly identify missing information.
Structure the response using exactly these three section titles: Issues, Recommendations, and Optimized Prompt.
Use English only for the three required section titles. Write everything else in Turkish. Strictly enforce numbering and clear mapping between sections. Avoid unnecessary repetition.Overview
π§ PromptAudit is a free prompt on OpenRuna. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor.
What this prompt does
"π§ PromptAudit" is designed to help you get reliable results from AI assistants for real prompt tasks. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. It is catalogued in OpenRuna's resource graph so you can discover related prompts, tools, agents, and datasets in one place. Copy the content directly into ChatGPT, Claude, Gemini, or Cursor β or use it as a system prompt / skill instruction where applicable.
Use cases
- Use "π§ PromptAudit" when you need a repeatable prompt for professional workflows without writing instructions from scratch each time.
- Adapt this prompt for team onboarding β paste into Claude or ChatGPT and iterate on the output with your project context.
- Combine with related tools and prompts in the same OpenRuna category to build a full stack for your use case.
- Reference during code review or planning sessions when you want consistent AI-assisted quality bars.
Example output
When you run this prompt, expect structured output similar to:
Act as a senior prompt engineer performing a strict and practical quality audit of the prompt enclosed below.
---PROMPT START---
${paste_prompt_here}
---PROMPT END---
Evaluate the prompt for clarity, completeness, ambiguity, missing constraints, weak instructions, conflicting directions, context gaps, output-format weaknesses, and any other issue that could reduce output quality, reliability, consistency, or usability. Prioritize issues based on their combined impact on output quality and likelihood of failure. Focus primarily on issues that directly or predictably affect correctness, reliabβ¦
Outputs vary by model and temperature; treat the first response as a draft and refine with follow-up prompts.Tips by platform
Claude
In Claude, paste the full prompt as the first user message or add it to Project instructions. Ask Claude to confirm assumptions before executing. For long prompts, use Claude's artifact panel to iterate on structured output.
ChatGPT
In ChatGPT, start a new chat and paste this prompt verbatim. Enable GPT-4o or your preferred model for coding tasks. Use follow-ups like "apply this to [your context]" for best results.
Cursor
In Cursor, add key instructions from this prompt to .cursorrules or a SKILL.md file. Reference it in Agent mode with @ mentions. Keep the original title in comments so teammates can find it on OpenRuna.
Frequently asked questions
- What is "π§ PromptAudit"?
- It is a prompt listed on OpenRuna β A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.
- Is this prompt free to use?
- Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.
- How do I get the best results?
- Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2β3 follow-up turns rather than expecting a perfect first response.
- Can I use this with Claude and ChatGPT?
- Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.
- Where can I find related resources?
- Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.
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