external-tools

Cross-model adversarial review validates AI-generated code by having a different AI model independently verify the implementation, reducing single-model blind spots. The orchestrator routes completed implementation tasks to a separate model for strict independent validation before committing changes.

You delegate implementation tasks using an orchestrator that runs health checks, selects the cheapest-available tool, and routes tasks to external AI CLIs like Codex or Gemini. The orchestrator enforces strict isolation, minimal permissions, and budget enforcement throughout the delegation process.

Yes, you can use Codex CLI and Gemini CLI together for cross-model code review. The orchestrator delegates implementation to one tool and routes the output to the other model for independent adversarial review, ensuring independent verification before integration.

External tool orchestration enforces cost limits and permissions through strict isolation, minimal permissions, budget enforcement, and artifact logging. The orchestrator selects the cheapest-available CLI tool for delegation and captures all results as factual outputs for accountability.

A limitation of cross-model adversarial review is its dependency on the availability and health of external AI CLI tools. The orchestrator runs health checks to select tools, but delegation and independent validation are constrained by budget enforcement and strict isolation requirements.