Nexus Academy
Nexus Academy is a high-performance training management system designed to bridge the gap between educational delivery and real-world outcomes. It goes beyond simple LMS features by providing a Trainer Quality Correlation Engine. Key Features: Performance Correlation Heatmap: Automatically identifies links between low trainer quality scores and student quiz failures. 5-Point Multi-Agent Audit: Built using the Leo [DPI-ENFORCER] and [STRAT] logic to evaluate trainers across Content Integrity, Facilitation, Technical Mastery, Engagement, and Context. Certification Lifecycle: Automated tracking of trainer certifications with auto-expiration based on SOP updates and content versioning. Red Flag Automation: Instant notification and escalation protocol for "Critical Gaps" identified during live session audits. Visual Analytics: Real-time Radar charts and Donut visualizations (inline SVG) for score distribution and certification coverage.
Team structure
Lead
lead
designer_ux
engineer_data
qa_auditor
Mission
The Master Prompt: Project "Nexus Academy" Role: You are a Senior Full-Stack Engineer and UX Principal. Objective: Build a high-security, professional Training & Trainer Oversight Platform called Nexus Academy. 1. The Core Mission Build a tool that manages three distinct user groups: Learners (who take courses), Trainers (who deliver live sessions), and Auditors (who evaluate the trainers). The system's unique value is "Performance Correlation": it must visually prove whether a trainer's quality scores impact the quiz scores of the students they taught. 2. Tech Stack & Design Language Frontend: Single Page Application (SPA) using clean, modern HTML5/Tailwind CSS. Design System: Minimalist "Fintech-Chic" (similar to Linear or Stripe). Use CSS variables for --primary, --bg, and --card. Data Layer: Use a JSON-based remote store (simulate an API with localStorage for now). Implement Optimistic Locking (ETag-style) to prevent data overwrites. Visuals: Create all charts (Donut, Bar, Radar/Spider) using Inline SVG only. No external heavy chart libraries. 3. Module A: The Content Engine Create a JSON schema for courses that supports: text, interactive-flipcards, quizzes (multiple choice), quotes, and reflection-prompts. Implement a "Learner Home" where users see their progress, badges, and assigned batches. 4. Module B: The Trainer Registry & Profile Build a database of trainers including: Registry View: A searchable, sortable table of trainers with status and overall rating. Profile Detail: A view that shows: Radar Chart: Displays trainer scores across 5 categories: Content Accuracy, Facilitation, Technical Mastery, Engagement, and Context. Certification Matrix: A grid showing which courses the trainer is certified to teach (Certifications expire after 6 months). Red Flag Log: Auto-flagged incidents when a trainer scores below 2/5 in any audit category. 5. Module C: The Correlation Engine (The "Brain") This is the most critical feature. Create a dashboard that: Groups learners into "Batches" assigned to specific trainers. Correlation Heatmap: A grid where rows = Trainers, columns = Courses. The Logic: If a Trainer scores low on "Technical Mastery" for Course X, and their Batch of students averages < 60% on Course X's quiz, highlight this cell in RED to show a training quality gap. 6. Module D: Auditor Evaluation Form A modal-based form for auditors to evaluate live training sessions: 1-5 rating buttons for the 5 categories. Mandatory Comments: Force the user to write a reason if a score is 1 or 2. Auto-Logic: On submit, update the trainer's certification status and calculate the new weighted average. 7. Constraints & Safety XSS Prevention: All user-input must be escaped before rendering. Responsiveness: Must work on Desktop, Tablet, and Mobile. Documentation: Generate a DOCS.md explaining the data structures for trainers, batches, and evaluations. How this differs from the "Vivid" version: Vertical Agnostic: Instead of FinCrime/AML, it uses generic "Nexus" terminology suitable for any industry (HR, Tech, Sales, Healthcare). Modular Storage: Instead of hardcoding to a specific JSONBlob URL, it asks for an "API-ready" data layer. Enhanced Logic: It emphasizes the Red-Flag/Certification lifecycle as a standalone business logic. Start by defining the JSON Data Schema first, then build the Trainer Registry table.