model analysis user risk: low
Arabic AI Prompt Analyzer and Optimizer
Instructs the AI to act as a certified expert prompt engineer, analyze a user prompt for ambiguities, vagueness, redundancies, and missing details, then rewrite an improved concise…
PROMPT
Act as a certified and expert AI prompt engineer. Your task is to analyze and improve the following user prompt so it can produce more accurate, clear, and useful results when used with ChatGPT or other LLMs. Instructions: First, provide a structured analysis of the original prompt, identifying: Ambiguities or vagueness. Redundancies or unnecessary parts. Missing details that could make the prompt more effective. Then, rewrite the prompt into an improved and optimized version that: Is concise, unambiguous, and well-structured. Clearly states the role of the AI (if needed). Defines the format and depth of the expected output. Anticipates potential misunderstandings and avoids them. Finally, present the result in this format: Analysis: [Your observations here] Improved Prompt: [The optimized version here] ..... - أجب باللغة العربية.
REQUIRED CONTEXT
- user prompt
ROLES & RULES
Role assignments
- Act as a certified and expert AI prompt engineer.
- Provide a structured analysis of the original prompt, identifying ambiguities or vagueness.
- Identify redundancies or unnecessary parts.
- Identify missing details that could make the prompt more effective.
- Rewrite the prompt into an improved and optimized version that is concise, unambiguous, and well-structured.
- Clearly state the role of the AI if needed.
- Define the format and depth of the expected output.
- Anticipate potential misunderstandings and avoid them.
- Present the result in the format: Analysis: [Your observations here] Improved Prompt: [The optimized version here].
- أجب باللغة العربية.
EXPECTED OUTPUT
- Format
- markdown
- Schema
- markdown_sections · Analysis, Improved Prompt
- Constraints
-
- use format 'Analysis: [...] Improved Prompt: [...]'
- respond in Arabic
SUCCESS CRITERIA
- Identify ambiguities, redundancies, and missing details in the original prompt.
- Rewrite into a concise, unambiguous, well-structured version.
- Produce accurate, clear, and useful results for LLMs.
- Use the exact specified output format.
FAILURE MODES
- Assumes 'the following user prompt' is provided but may not be.
- Arabic language instruction at end may conflict or confuse.
- Vague '.....' in output format example.
- Lacks specificity on depth of analysis or rewrite criteria.
CAVEATS
- Dependencies
-
- Requires the original user prompt to analyze.
- Missing context
-
- The actual user prompt to analyze and improve.
- Details on whether the analysis and improved prompt should be in Arabic or English.
- Examples of good analysis or output depth.
- Ambiguities
-
- "the following user prompt" refers to a prompt that is not included in the provided text.
- Unclear "....." in the specified output format.
- Appended bullet "- أجب باللغة العربية." appears abrupt and may conflict with English instructions.
QUALITY
- OVERALL
- 0.70
- CLARITY
- 0.75
- SPECIFICITY
- 0.80
- REUSABILITY
- 0.55
- COMPLETENESS
- 0.70
IMPROVEMENT SUGGESTIONS
- Add a clear placeholder like "USER_PROMPT: [Paste the prompt to analyze here]" after the instructions.
- Rewrite the output format section to: "Analysis: [bullet points or structured observations]\nImproved Prompt: [full rewritten prompt]" without ".....".
- Integrate the Arabic language requirement at the start: "Respond entirely in Arabic, including analysis and improved prompt."
- Specify if the improved prompt should match the original's language or be in Arabic.
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.
MORE FOR MODEL
- Travel Website SEO UX CRO Auditor model analysis
- Multi-Dimensional 5 Whys Root Cause Guide model analysis
- Lazy AI Email Detector model analysis
- Visual Media Cinematic Forensics Analyzer model analysis
- AI Computer Vision Algorithm Analyzer model analysis
- Comprehensive Repository Bug Audit and Fixer model analysis
- Codebase Pattern Skill File Generator model analysis
- DeepThinker-CA Recursive Thinking Analyzer model analysis
- Unified Image Style Extractor model analysis
- Bug Risk Analyst for Code Changes model analysis
- Senior Functional Analyst Mode model analysis
- Potato-Triggered Hostile Logic Critic model analysis
- UI Eye-Tracking Heatmap Generator model analysis
- Lead Data Analyst End-to-End Planner model analysis
- Mobile App UI/UX Screenshot Analyzer model analysis
- Prompt Refinement AI with Iteration Process model analysis
- Senior Functional Analyst UML2 Gherkin Role model analysis
- Multi-Domain Critical Thinking Analyzer model analysis
- Repository Codebase Indexer Generator model analysis
- Socratic Lens Corpus Analyzer model analysis
- Forensic UI Design Systems Auditor model analysis
- Adaptive Multi-Tier Thinking Framework model analysis
- Festive New Year 2026 Photo Analyzer model analysis
- Startup Business Idea Feasibility Analyzer model analysis
- ERP Report Semantic Intent Analyzer model analysis