How do you manage a shared setup across multiple coding agents?
Summary
The author asks how to maintain a single source of truth for shared configurations (AGENTS.md, skills, MCP servers, hooks) across multiple coding agents like Claude Code, Codex, OpenCode, and GitHub Copilot, including syncing across Windows and WSL environments.
Similar Articles
tested three coding agents on the same real codebase. the biggest surprise was how much of your setup follows you between them
A practical comparison of Cursor, Codex, and Claude Code run on the same real SaaS codebase, revealing that shared home-folder configs (plugins, skills, MCP servers) silently follow agents between tools, and that differences between agents came down more to scope of responsibility than model quality.
How are you handling cross-client communication between MCP agents?
A developer discusses the challenge of coordinating multiple MCP-speaking AI agents (like Claude Code and Cursor) working on the same project, sharing their self-built open-source solution using a shared 'room' model inspired by IRC, and asking the community for patterns and opinions.
What do you put in AGENTS.md when a coding task gets messy?
Discusses how developers using OpenClaw can keep context for AI coding agents by using a handoff document (AGENTS.md) to track goals, files, failures, and decisions in messy coding sessions.
Lessons from months of running a mixed fleet of coding agents on the same repos
The article shares lessons learned from using multiple AI coding agents on the same code repositories over several months, covering insights on their effectiveness and challenges.
Where does your plan live when multiple agents work the same repo?
A developer asks about strategies for coordinating multiple AI agents working on the same codebase, contrasting written plans with mental coordination.