Hmm, maybe it's just me, but it's a good thing the different agents use different files, different models needs different prompts. Using the same system/user prompts across all three will just give you slightly worse results in one of them, instead of getting the best results you can from each one of them. At least for the general steering system prompts.

Then for the application specific documentation, I'd understand you'd want to share it, as it stays the same for all agents touching the same codebase. But easily solved by putting it in DESIGN.md or whatever and appending "Remember to check against DESIGN.md before changing the architecture" or similar.

I did create and actively use a similar tool, but with different purpose: configure AI tools for each team member to use the same code style and architecture guides across projects. It includes: - build docker images for claude code and opencode dev containers. - creates custom MCP server that works as a proxy and combines several tools into a single one ( for example, web search, fetch, and context7 tools exposed as a single "web_research" that invokes custom code to answer question ) - copy code style, documentation, and best practice rules for technologies used in our projects - deploys a bunch of helper scripts useful for development - configure agents, skills, hooks, and commands to use those rules. Configuration changed per "mode" : documentation, onboarding, code review, and web development all have different settings. - run AI tools in docker container with limited permissions - feedback tool to generate session report, that is used for automatic evaluation and prompt optimization.

This came out of necessity, as active using of AI assistants in uncontrollable way significantly degraded code quality. The goal is to enforce the same development workflow across team This is internal tool. If someone interesting, I can create a public repo from it

Is this substantially different than https://github.com/intellectronica/ruler? Or how would you differentiate?

This is interesting, but I’m now at a point where I can tell Claude/GPT to “take this skills and prompts repo and adapt them to this project” and it will just do it and out all the files in the right place… so a tool to do this seems redundant right now.

I really like the idea of an agent package manager! I built something similar aiming to be like uv but for AI agents https://github.com/kasperjunge/agent-resources

This solves distribution well. Curious about the change propagation story though - what happens when you update your .ai/ source and tools have cached/transformed versions?

I ran into this building a spec/skill sync system [1] - the "sync once" model breaks down when you need to track whether downstream consumers are aware of upstream changes.

  [1] https://github.com/anupamchugh/shadowbook

Nice. The config fragmentation across tools is a real annoyance Does it handle conflicts if tools expect different formats for the same setting?

I've been using Claude Code, Cursor, and Codex on the same projects. Each tool has its own config format: Claude wants `.claude/`, Cursor wants `.cursor/`, Codex wants `.codex/`. Every time I updated a skill/rule, I had to update it in 3+ places. Usually I'd forget one, and my tools would give inconsistent suggestions. LNAI is a CLI that lets you define your AI configs once in a `.ai/` directory:

.ai/ ├── AGENTS.md ├── rules/ ├── skills/ └── settings.json # MCP servers, permissions

Run `lnai sync` and it exports to native formats for 7 tools: Claude Code, Cursor, GitHub Copilot, Gemini CLI, OpenCode, Windsurf, and Codex. The interesting part is it's not just copying files. Each tool has quirks:

- Cursor wants `.mdc` files with `globs` arrays in frontmatter - Gemini reads rules at the directory level, so rules get grouped - Permissions like `Bash(git:*)` become `Shell(git)` for Cursor - Some tools don't support certain features (e.g., Cursor has no "ask" permission level). LNAI warns but doesn't fail

Where possible, it uses symlinks. So `.claude/CLAUDE.md` → `../.ai/AGENTS.md`. Edit the source, all tools see the change immediately without re-syncing.

Usage:

npm install -g lnai lnai init # Creates .ai/ directory lnai validate # Checks for config errors lnai sync # Exports to all enabled tools

It's MIT licensed. The code is TypeScript with a plugin architecture, each tool is a plugin that implements import/export/validate. GitHub: https://github.com/KrystianJonca/lnai Docs: https://lnai.sh

Would appreciate feedback, especially from anyone else dealing with this config hell problem.

How is this different than Agents.md? Isn’t it just easier just to have one agents.md file?

I’ve been using chezmoi to manage dot files, that should be enough to handle AI config too. It’s easier to just have one tool do all of that.

I need to install npm in order to use AI agents? No, thanks.