What problem does it solve? Running code reviews across multiple quality dimensions often produces overlapping findings, inconsistent severity ratings, and fragmented reports that are hard to act on. This Skill provides structured patterns for organizing multi-reviewer reviews, merging duplicate findings, calibrating severity, and producing a single consolidated report. ## Core Features & Use Cases - Review Dimension Allocation: Choose the right review dimensions (Security, Performance, Architecture, Testing, Accessibility) based on the type of change, with recommended combinations for common scenarios like API endpoints, frontend components, and database migrations. - Finding Deduplication: Apply deterministic merge rules for findings at the same file and line, handling conflicting severities and recommendations with reviewer attribution. - Severity Calibration: Use consistent criteria mapping impact and likelihood to Critical, High, Medium, and Low ratings, with domain-specific calibration rules. - Consolidated Reporting: Generate a standardized review report with findings grouped by severity and a per-dimension summary table. - Use Case: When reviewing a pull request that adds a new authenticated API endpoint, assign Security, Performance, and Architecture reviewers, merge their overlapping findings, calibrate severity, and output one prioritized report. ## Quick Start Organize a multi-dimension code review of my latest pull request covering security, performance, and architecture, then consolidate the findings into a single severity-ranked report.
