multi-model-validation

Parallel model execution lets you send code or designs to Grok, Gemini, GPT-5, DeepSeek, or Claudish proxies simultaneously, then aggregate their feedback into a consensus report. This eliminates sequential bottlenecks and provides multi-perspective validation 3-5x faster than serial reviews.

Yes. Use claudish --top-models and claudish --free to dynamically discover current available models, then select internal and external models for your validation session without manual configuration.

Session-based workspaces isolate each validation run and capture timing, success/failure rates, and model performance metrics. These statistics drive data-driven recommendations for model curation and reveal which models perform best on your workloads.

Create a unique session directory for each validation run. Session-based workspaces automatically isolate input, outputs, and intermediate results per session, preventing cross-contamination between concurrent or sequential reviews.

Yes. Mandatory checklists ensure complete reviews across all selected models, and timing instrumentation with SubagentStop hooks track execution progress. The 4-Message parallel execution pattern and Pattern 7-8 analytics satisfy enforced compliance and performance discipline.

Consensus-driven validation aggregates findings from multiple models running in parallel, reducing bias and false positives. Single-model review is slower and prone to individual model blind spots; parallel execution captures diverse perspectives in one consolidated report.