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To automate multi-agent code review, you orchestrate parallel specialist sub-agents that analyze git diffs and consolidate findings. This automated triage selects specialist reviewers based on project context, producing a structured, reproducible report with severity-based categorization.

Adversarial testing in automated code review rigorously probes for edge cases, concurrency issues, and security vulnerabilities. It applies an adversarial mode within the multi-agent workflow to stress-test git diffs beyond standard quality assurance checks.

Yes, parallel code review supports security analysis across diverse codebases by delegating to specialist sub-agents. It applies to software development lifecycles requiring automated triage, analyzing git diffs to identify and consolidate security findings.

Automated reviewer selection works by analyzing git diffs and matching code changes to project-specific agent definitions. The orchestration workflow delegates review tasks to the most relevant specialist sub-agents for targeted quality assurance.

Yes, project-specific agent definitions are required to enable automated reviewer selection. The multi-agent code review workflow uses these definitions to delegate findings to specialist sub-agents and produce structured, reproducible review documentation.

Automated multi-agent code review depends on the quality of project-specific agent definitions and git diff accuracy. It is designed for structured triage and security analysis, meaning complex logic errors outside diff context may require manual verification.