What problem does it solve? Preparing for a Netflix Data Science Engineering interview often starts with unstructured thinking — framing questions, half-formed stories, quick concept lookups — that doesn't fit a formal mock, drill, or STAR-building session. This Skill provides a low-friction conversational coaching mode that captures insights continuously and routes to structured skills when the conversation matures. ## Core Features & Use Cases - Free-form coaching conversation: Think out loud, explore framings, and get 2-3 angle options per question without role-play, scoring boxes, or forced STAR templates. - Continuous knowledge-base capture: Verbatim quotes, story seeds, gaps, and culture-resonance updates are persisted to knowledge-base/ files with single-line confirmations. - Routing to structured skills: When a conversation matures into a story, mock, drill, or formal answer review, the coach offers a route to star-story-builder, answer-gap-analyzer, interview-* mocks, or netflix-scenario-drill. - Session logging: Auto-writes a re-readable session log to interviews/coach-chat-<date>-<NN>.md with frameworks taught, story walkthroughs, and prioritized follow-ups. - Use Case: You ask "how should I frame my semantic-layer work for the product-sense round?" and receive three framings tied to specific interviewers, then get routed to a STAR session once the story solidifies. ## Quick Start Ask the coach to talk through how you should frame one of your past projects for a Netflix interviewer.
