What problem does it solve? Behavioral interview answers often come out unstructured, vague, or missing quantified results. This Skill walks you through turning a raw experience into a polished STAR story (Situation, Task, Action, Result) with metrics, Netflix value mapping, and predicted interviewer follow-up questions, then persists it to a reusable knowledge base. ## Core Features & Use Cases - Guided STAR walkthrough: Interactively extracts situation specifics, isolates what you personally owned, converts "we" to "I" actions, and pushes for quantified results without fabricating missing metrics. - Netflix value mapping and probe prediction: Identifies which Netflix values the story lands on, lists 2-4 follow-up questions an interviewer will ask, and tracks weak spots for later coaching. - Persistent story library: Writes each story to knowledge-base/stories/<slug>.md using a structured template and keeps INDEX.md in sync, with interviewer-specific variants (HM, peer, director). - Use Case: Before a Netflix onsite, you describe a messy migration project in your own words; the Skill produces a 3-minute STAR story with a latency metric, Selflessness framing, and three anticipated probes. ## Quick Start Ask the assistant to build a STAR story about a specific experience, for example: "Build a STAR story about the time I led the pipeline rewrite."
