bmad-code-review

Execute parallel adversarial code review layers on git diffs and project documentation.

Updated Jul 11, 2026
One-click install
npx skills add https://github.com/marcmontecalvo/kinward --skill bmad-code-review-marcmontecalvo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-code-review
Source: https://github.com/marcmontecalvo/kinward/tree/main/.agents/skills/bmad-code-review
Command: npx skills add https://github.com/marcmontecalvo/kinward --skill bmad-code-review-marcmontecalvo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) components.

What problem does it solve?

This skill addresses the inconsistency and oversight common in manual code reviews by implementing a rigorous, multi-layered adversarial analysis process that ensures code quality and adherence to specifications.

Core Features & Use Cases

  • Parallel Adversarial Review: Simultaneously runs Blind Hunter, Edge Case Hunter, and Acceptance Auditor layers to identify bugs, logic flaws, and spec deviations.
  • Structured Triage: Automatically categorizes findings into actionable buckets like patches, decisions needed, or deferred items to streamline the remediation process.
  • Sprint Integration: Syncs review outcomes directly with sprint tracking files to maintain project velocity and visibility.

Quick Start

Trigger the review process by telling the assistant to run code review on the current changes.

Frequently Asked Questions about bmad-code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate adversarial code review on git diffs?

Adversarial code review on git diffs is automated by running parallel analysis layers that identify bugs, logic flaws, and specification violations, providing structured triage for software development workflows.

What is multi-layer triage in automated code review?

Multi-layer triage in code review automatically categorizes identified issues into actionable buckets like patches, decisions needed, or deferred items to streamline the remediation process.

How do I ensure automated code reviews catch edge cases and spec deviations?

Automated code reviews catch edge cases and spec deviations by executing parallel Blind Hunter, Edge Case Hunter, and Acceptance Auditor analysis layers against project documentation and local git state.

Do I need local git state and project configuration files for context-aware code validation?

Context-aware code validation requires access to local git state, project configuration files, and sprint tracking artifacts to ensure reviews are synced with project velocity and specifications.

How does automated code review integrate with sprint tracking files?

Automated code review integrates with sprint tracking files by syncing review outcomes directly, maintaining project velocity and visibility throughout the development workflow.

What are the limitations of python3-based automated code triage?

Python3-based automated code triage is limited by its dependency on local git state and specific sprint tracking artifacts, requiring precise project configuration to ensure context-aware validation.