jd_optimization

What problem does it solve?

This skill improves AI-generated or recruiter-edited job descriptions by making them SEO-friendly, ATS-compliant, readable, and conversion-focused so recruiters get higher-quality applicant flows.

Core Features & Use Cases

• SEO and Keyword Optimization: Ensure titles and descriptions include primary and semantic keywords, location data, and structured data recommendations for Google for Jobs.
• ATS Compliance & Readability: Enforce plain formatting, standard headers, and readability targets (Flesch score and sentence length) to maximize parsing success and candidate comprehension.
• Conversion Enhancements & Workflow Integration: Add compelling hooks, salary transparency, remote/hybrid signals, and integrate with regenerate-jd APIs and LangGraph checkpoints to iterate on JDs before posting.
• Use Case: A recruiter reviews an AI-generated JD, triggers regeneration with focused feedback to add salary range and remote details, and publishes an optimized JD to LinkedIn and job boards.

Quick Start

Regenerate the job description with feedback asking to include a salary range, emphasize remote work options, and mention FastAPI and LangGraph in the tech stack for better SEO and ATS compatibility.