This Epic covers the integration of our centralized AI Reviewer (located in core/tools/ai-review) across the RHEL-AI ecosystem.

Rather than building new logic, the task is to "teach" the reviewer how to handle each specific repository by creating tailored SKILL.md files and adding the necessary GitLab CI job calls to trigger the centralized reviewer.

Implementation Plan

1. Skill Development (SKILL.md)

For each repo, a SKILL.md must be defined to provide context to the AI (e.g., coding standards, specific tech stacks, or architectural constraints).

• Code Repos: Focus on Python/Container best practices.

• Docs/ADR: Reuse/refine the existing skill logic in architecture-decision-records.

• Pipelines: Focus on GitLab CI syntax and YAML optimization.

2. CI/CD Integration

Add a job to each repository’s .gitlab-ci.yml that:

1. Triggers/calls the utility in core/tools/ai-review.

1. Passes the local SKILL.md as context for the review.