ATS Keyword Injection Engine for Resume Optimization

By framing the LLM as an ATS optimization system, you prime it to focus specifically on keyword alignment — the primary mechanism ATS tools use to score resumes. This role-assignment anchors the model's output to a well-understood professional task rather than a vague editing job. The explicit constraints (no keyword-stuffing, high readability, human tone) prevent the most common failure mode of naive keyword injection, where text becomes robotic or repetitive. These guardrails push the model to integrate keywords contextually into existing bullet points and descriptions rather than appending keyword lists. Asking for a separate list of added keywords serves two purposes: it creates accountability (you can verify nothing inappropriate was inserted) and gives you a checklist to cross-reference against the original job description for any gaps.