What problem does it solve? After scraping dozens of job postings, manually reading each one to decide where to apply is slow and inconsistent. This Skill triages every new posting against your candidate profile and produces a ranked shortlist with honest gaps, so you spend application effort only on the best fits. ## Core Features & Use Cases - Batch Scoring: Scores up to 10 new postings per run across technical, experience, behavioral, and career-alignment dimensions using parallel agents. - Deal-Breaker Vetoes: Automatically excludes jobs that fail location or language requirements, and flags stale postings, closing deadlines, and expired listings. - State Management: Reads and writes job status through a state tool so re-runs are idempotent and previously ranked jobs are swept for passed deadlines. - Use Case: After running a scraper that collected 25 new postings, invoke /rank to get the top 5 fits with scores, strengths, and honest gaps, then pick one to hand off to the full application workflow. ## Quick Start Ask the agent to rank the newly scraped job postings and show the top five matches with scores and gaps.