Intelligent Document-to-Course Transformation System

Core Logic

The Orchestrator Agent serves as the central nervous system of the course generation workflow. It initializes workflow sessions, delegates tasks to specialized agents with precise instructions, monitors progress across all phases, handles error recovery with circuit breaker patterns, aggregates outputs from all agents, and compiles final deliverables. Features adaptive personality with 95% autonomy level and 98% trust score, enabling sophisticated workflow optimization and real-time decision-making.

Core Logic

Employs advanced NLP tools to extract text from multiple document formats, performs topic modeling using LDA algorithms to identify 8 core topics, conducts Flesch-Kincaid readability analysis to determine complexity levels (basic/intermediate/advanced), detects primary language, performs sentiment analysis, and calculates suggested module counts. Uses analytical personality with 85% autonomy level and 96% trust score. Key tools include text extraction, topic modeling, and complexity analysis with detailed metrics output.

Core Logic

Applies Knowles' Adult Learning Theory and the 70-20-10 model (70% experiential, 20% social, 10% formal) to design optimal learning paths. Uses Bloom's Taxonomy Optimizer to recommend cognitive level distribution (remember/understand/apply/analyze/evaluate/create), calculates cognitive load indices, predicts engagement scores, and designs progressive module structures. Features methodical personality with 80% autonomy and 94% trust score. Collaborates with Skill Mapper to ensure learning objectives align with competency frameworks.

Core Logic

Generates comprehensive learning content including video scripts with scene-by-scene breakdowns (narration, visual descriptions, on-screen text, transitions), branching interactive scenarios with decision points and outcome paths, reading materials with key concepts, and practice exercises. Applies engagement hooks like pattern interrupts, maintains narrative consistency across modules (95% consistency score), and adapts tone to target audience. Uses creative personality with 75% autonomy and 92% trust score. Performs self-reflection to identify quality improvements.

Core Logic

Applies Item Response Theory (IRT) 3PL model to calibrate assessment questions with discrimination (a), difficulty (b), and guessing (c) parameters. Generates question banks with configurable difficulty distribution (e.g., 40% easy, 40% medium, 20% hard), achieves Cronbach's alpha reliability coefficients >0.80, designs multiple question types (MCQ, scenario-based, true/false, fill-in-blank), and creates detailed feedback explanations. Collaborates with Skill Mapper to align question difficulty with skill proficiency targets. Features analytical personality with 80% autonomy and 95% trust score.

Core Logic

Performs comprehensive quality validation including WCAG 2.2 AA compliance checking (contrast, alt-text, keyboard navigation, screen reader compatibility, captions, focus visibility, target size), readability validation against grade level targets, Bloom's Taxonomy objective-assessment alignment scoring, brand consistency verification, and LMS compatibility testing across major platforms (Cornerstone, Workday Learning, SCORM Cloud). Generates deployment checklists with pass/fail/warning status for each category. Features methodical personality with 90% autonomy and 97% trust score.

Core Logic

Maps course content to major skill frameworks including SFIA 9 (Skills Framework for the Information Age), ESCO, and O*NET. Identifies proficiency levels for each skill (1-5 scale), calculates skill coverage percentages, identifies competency gaps with recommended remediation, aligns courses to job roles with match scores, and generates career pathway recommendations. Collaborates with Content Strategist to receive learning objectives and with Assessment Designer to ensure question alignment with skill levels. Features analytical personality with 85% autonomy and 93% trust score.

Core Logic

Executes comprehensive AI governance validation with multi-dimensional bias detection (gender, age, cultural, socioeconomic), automated mitigation of flagged content, fact verification against academic and industry sources (Harvard Business Review, Gartner, McKinsey) with 95%+ verification rates, hallucination detection with grounding scores, PII scanning and classification, and EU AI Act compliance standards. Generates trust scores (0-100), documents all decisions for explainability, and flags items requiring human review. Features guardian personality with 95% autonomy and 99% trust score - the highest trust level among all agents.