What problem does it solve? Raw user interview transcripts contain scattered scenarios and needs that are hard to turn into actionable product innovation inputs. This Skill structures any interview transcript into a logically self-consistent table covering category, opportunity, persona, need, benefit, perceptible experience parameter, and counterintuitive user insight. ## Core Features & Use Cases - Seven-Step Extraction Workflow: Reads the full transcript, builds user personas, decomposes scenario-based needs per category, defines benefits, quantifies experience parameters, and closes with counterintuitive insights plus a completeness audit. - Seven-Field Structured Output: Produces a Markdown table with category lifecycle, opportunity gaps, three-dimensional personas, surface vs. deep needs, benefit statements, quantified perceptible experience parameters, and behavioral-paradox insights. - Self-Consistency Checklist: Enforces validation rules such as quantified parameters, deep-need-driven benefits, and anti-cliche insight conclusions before output. - Use Case: Paste a consumer interview transcript about a smart thermos or lipstick product, and receive a row-per-need table that product teams can feed directly into concept definition and technology planning. ## Quick Start Analyze this user interview transcript and output the seven-field perceptible experience parameter table with one row per distinct need.
