[FEATURE]: Support multi-LLM parallel review for /reviews command #6078

Feature hasn't been suggested before.

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Describe the enhancement you want to request

Problem / Motivation : Currently, the /reviews command likely uses a single LLM to provide feedback. However, different models (e.g., GPT-5, Claude 4.5 Sonnet, DeepSeek-V3) have different strengths, such as code logic analysis, security vulnerability detection, or style consistency. Relying on a single model may lead to biased or incomplete reviews.

Proposed Solution : I suggest enabling the /reviews command to trigger multiple LLMs simultaneously. The system should:
Allow users to specify multiple models in the command or configuration.
Execute the review tasks in parallel.
Consolidate the findings from all models into a single, comprehensive summary report.

Benefits :
Comprehensive Insights: Capture a wider range of potential issues.
Cross-Verification: Reduce false positives by comparing results across models.
Flexibility: Users can choose the best model combination for their specific tech stack.