agentsmesh

Generate native tool configurations from a unified .agentsmesh/ workspace.

Updated May 4, 2026

Search Tags:#automation #devops #canonical #config-generation #multi-tool #agentsmesh #tool-configs

Ready to run

npx skills add https://github.com/rigerc/repo-2 --skill agentsmesh

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agentsmesh
Source: https://github.com/rigerc/repo-2/tree/main/.agents/skills/agentsmesh
Command: npx skills add https://github.com/rigerc/repo-2 --skill agentsmesh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Managing AI tool configurations across multiple platforms is error-prone and time-consuming. AgentsMesh provides a single canonical source of truth for all tool configurations, ensuring consistency and reducing drift.

Core Features & Use Cases

Centralized configuration: edit once to generate tool-specific configs for all targets.
Extensible rule, hook, and extension system for per-project customization.
Use case: unify settings for Claude Code, Cursor, Copilot, Gemini CLI, and more, then generate tool configs across tools.

Quick Start

Edit the canonical .agentsmesh/ files and run the generate workflow to produce tool-specific configurations.

Frequently Asked Questions about agentsmesh

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I manage multiple AI tool configurations without drift across Cursor and Claude Code?▼

Consolidating fragmented AI tool configurations into a single canonical source prevents drift. AgentsMesh lets you edit once inside a .agentsmesh/ workspace and generate tool-specific configs for Cursor, Claude Code, and others.

What is the best way to generate native configs for multiple AI coding tools from one source?▼

Generating native AI tool configurations from one source requires a canonical workspace. AgentsMesh applies a unified model to generate tool-specific settings across platforms like Copilot, Gemini CLI, and Codex CLI.

Can I apply per-project and per-developer overrides when unifying AI tool configs?▼

Yes, applying per-project and per-developer overrides is supported. AgentsMesh allows you to define custom rules, hooks, and feature sets inside the canonical .agentsmesh/ workspace for consistent generation.

Does a unified config source work with both CLI and editor-based AI coding assistants?▼

A unified config source works across both CLI and editor-based AI assistants. AgentsMesh applies settings to projects managing multiple tools including Claude Code, Cursor, Copilot, Gemini CLI, and Codex CLI.

How do I start using a canonical .agentsmesh/ workspace to configure my AI tools?▼

To start using a canonical .agentsmesh/ workspace, edit the canonical files directly and run the generate workflow. This processes your unified model to produce tool-specific configurations across your development tools.

Why do my AI tool configurations drift when working across multiple platforms like Cursor and Gemini CLI?▼

AI tool configurations drift because managing fragmented settings across multiple platforms is error-prone. AgentsMesh solves this by providing one canonical source of truth to generate tool configs and ensure consistency.