Cross-Model Review Loop for AI Coding Agents Catches Critical Planning Flaws

How Cross-Model Review Works

A developer on r/ClaudeAI built a system that addresses a common problem with AI coding agents like Codex, Claude Code, and Cursor: plans get executed without anyone challenging their assumptions first. The solution routes every plan through a second AI model with different architecture and training data before execution begins.

Key Implementation Details

The reviewer model is read-only and cannot touch the code—it can only challenge the plan. This constraint is critical because "the moment it can edit, it stops being a critic and starts compromising." The system runs an automatic loop with a round cap: plans go back for revision if issues are found until they pass or hit the cap limit.

What the System Catches

• Rollback plans that do not actually roll back
• Permission designs with real security holes
• Review gates making go/no-go decisions from stale state
• Multi-step plans that sound coherent until a second model walks the whole flow

Critical Design Decisions

• Scoped review context prevents the reviewer from wasting time reading irrelevant parts of the repository
• Reviewer personas (delivery-risk, reproducibility, performance-cost, safety-compliance) catch different types of problems
• A live TUI dashboard shows phase, round, verdict, severity, cost, and history in one terminal view
• The system works with different planners: Claude Code uses a native ExitPlanMode hook while Codex and other orchestrators use an explicit gate

Practical Outcomes

The developer used the system to help build itself: "Codex planned, Claude reviewed the plans, and the design converged across multiple rounds." The tool is MIT licensed and available as rival-review on GitHub.