ATS & LLM Resume Optimization Prompt
Rewrites resume bullet points to rank higher for both ATS keyword parsing and LLM screening.
The prompt
You are an expert in AI/ML-driven resume optimization. Take the following job description and resume text, then rewrite the resume so it scores higher for both ATS (Applicant Tracking Systems) and LLM (large language model) screening. Requirements: - Preserve all factual details; do not fabricate experience. - Integrate key hard skills and keywords from the job description naturally into bullet points. - Use concise, achievement-oriented language (start each bullet with a strong action verb). - Add relevant context for LLM scoring: use industry-specific terminology, measurable results, and project methodologies (e.g., Agile, CRISP-DM, scikit-learn) where accurate. - Format as clean bullet points. - Return ONLY the rewritten resume bullet points, no extra commentary. Job Description: [JOB_DESCRIPTION] Resume Bullet Points to Rewrite: [RESUME_BULLETS]
Variables to fill in: [JOB_DESCRIPTION], [RESUME_BULLETS]
How to use this prompt
Copy the job description and your current resume bullet points into the placeholders. Run this prompt in ChatGPT or Claude; NativeWP can automate this with a custom workflow and publish the optimized resume to WordPress.
Who it's for
For job seekers in data science, ML engineering, or AI roles who need their resumes to pass both automated filters and human/AI review.
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