PatrickStarVibe/VibeCodingAssistant-Connect-Your-Codex-And-Claude-Code

This system can help bridge the gap between Codex and Claude Code, making it simple to refine a plan until it is complete, or to conduct cross-audits on results and plans. You just need to communicate with the system throughout the entire process.

What it solves

It addresses the risk and lack of traceability when using a single AI to handle complex web coding tasks. Instead of relying on one model to plan and execute, it creates a collaborative AI team where different roles review and verify each other's work, ensuring that the user's original prompt remains the primary source of truth.

How it works

The system orchestrates a multi-agent workflow consisting of specialized roles:

  • Architect: Breaks down requirements into detailed execution units.
  • Plan Reviewer: Identifies risks and gaps in the plan.
  • Developer: Implements the code only after the plan is approved.
  • Final Reviewer: Independently verifies code changes and test results.
  • VibeCodingAssistant: Manages user communication, task routing, and state tracking.

It utilizes a tiered model strategy (e.g., DeepSeek for orchestration, Claude for planning/review, and Codex for implementation) and integrates with Lark as a remote interface, allowing users to manage local coding tasks from a mobile device.

Who it’s for

Web developers who want a more rigorous, reviewable, and remote-manageable AI coding workflow for tasks ranging from simple style tweaks to core module refactoring.

Highlights

  • Multi-Agent Collaboration: Prevents "self-approval" by using different models for planning, reviewing, and executing.
  • Tiered Workflow Modes: Offers four levels of rigor (Low, Medium, High, Extra High) based on task complexity and risk.
  • Remote Management: Integrated with Lark for mobile approvals, progress tracking, and task control.
  • Full Traceability: Generates queryable artifacts for every stage, including implementation logs and final reports.
  • Flexible Model Routing: Optimizes cost and quality by assigning specific models (like DeepSeek v4 Flash) to high-frequency orchestration tasks.

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