What should I do if the AI reviewer identifies a critical issue?

Critical and important issues should be addressed immediately before proceeding to the next task to prevent technical debt and cascading errors.

When should I trigger a code review using this skill?

It is recommended to request a review after completing each task in a subagent-driven workflow, after finishing major features, or as a final check before merging to the main branch.

Can I challenge the feedback provided by the AI subagent?

Yes. If the reviewer is incorrect, you should push back with technical reasoning, provide code examples, or run tests to justify your implementation.

How does the subagent know which code to audit?

The skill utilizes Git SHAs (Base and Head) to define the exact range of commits that represent the new implementation, ensuring the subagent focuses only on relevant changes.

AI Code Review Dispatcher

Name: AI Code Review Dispatcher
Author: franroa

byfranroa

Herramientas de Colaboración

Dispatches a specialized code-reviewer subagent to identify implementation issues and verify requirements before code is merged.

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The AI Code Review Dispatcher streamlines the quality assurance process by triggering a dedicated subagent to audit code changes against specific plans or requirements. By leveraging git SHAs to isolate implementation details, it provides targeted feedback on architectural integrity and bug prevention. This skill is essential for maintaining high standards in subagent-driven development, allowing developers to catch critical errors early in the cycle and ensure that every feature meets its defined technical criteria before reaching the main branch.

Características Principales

0 GitHub stars
Categorized feedback loops for critical, important, and minor improvements
Automated subagent dispatching for targeted technical audits
Seamless git integration using commit SHAs for precise change tracking
Requirement-to-implementation verification to ensure task compliance
Adaptive workflow support for both ad-hoc and subagent-driven development

Casos de Uso

Verifying individual task completion during complex feature implementation
Gaining a fresh technical perspective when stuck on complex debugging or refactoring
Performing a final automated audit before merging feature branches into main

Acerca de

Características Principales

0 GitHub stars
Categorized feedback loops for critical, important, and minor improvements
Automated subagent dispatching for targeted technical audits
Seamless git integration using commit SHAs for precise change tracking
Requirement-to-implementation verification to ensure task compliance
Adaptive workflow support for both ad-hoc and subagent-driven development

Casos de Uso

Verifying individual task completion during complex feature implementation
Gaining a fresh technical perspective when stuck on complex debugging or refactoring
Performing a final automated audit before merging feature branches into main