Enables multi-model code review by fanning out issues to multiple LLMs simultaneously, diffing their unique insights, optionally running debate rounds, and dispatching subagents to implement fixes with git commits.
Enables multi-agent code review with P0/P1/P2 severity scoring by orchestrating locally installed AI CLIs (Claude, Codex) to perform parallel analysis, deterministic scoring, and consensus-building on git diffs.
Enables multi-agent code review with cross-verification of findings against source code, catching hallucinations and improving agent accuracy over time.
Enables AI-powered code review and improvement, including analysis, refactoring suggestions, and automatic test generation, with an optional agentic loop for iterative refinement.
A multi-persona code review tool that leverages AI agents with distinct expertise (Codex, Toxic Architect, Accessibility Expert) to analyze code quality through the Model Context Protocol.
