Aureon:Software Project Management and Technical Quality Monitoring

Software engineering organizations frequently evalu-ate agile delivery progress, code repository activity, static source code quality, and technical debt risks using disparate, discon-nected tools. This fragmentation creates semantic dissonance across teams, obscures early architectural decay, and impairs objective governance. This paper presents Aureon, a web-based software engineering intelligence framework that integrates agile sprint and task management, automated GitHub repository synchronization, multi-metric static code analysis via Radon and Pylint, rule-based technical debt tracking, and role-specific operational dashboards. Aureon computes a deterministic, multi-pillar Project Health Score (H) aggregated across four normalized engineering dimensions: sprint delivery health (S), repository development cadence (G), static code quality (Q), and technical debt risk (D). In addition, the framework formulates an objective developer-task suitability index (T ) based on skill coverage, task concurrency capacity, and remaining schedule availability. This study conducts an extensive critical review of 19 peer-reviewed software engineering papers published between 2025 and 2026, articulates an evidence-supported research gap in consolidated and interpretable metric aggregation, and defines a rigorous empirical evaluation methodology that cleanly isolates verified deterministic mechanics from future predictive extensions. Automated tests (64 passing test suites), clean production builds, and verified operational pathways validate structural correctness while establishing clear empirical boundaries.