Universal AI agent orchestration toolkit that transforms any AI coding assistant into a coordinated fleet of specialist agents.
OmniRule is easy to set up with trust notes worth reviewing. Check agent compatibility and use-case fit before adding it to your workflow.
npx skills add mikailustuner/OmniRuleRun the command in your terminal.
Confirm that the skill files were added to your agent workspace.
Check the README requirements before invoking the skill in your agent.
OmniRule is a toolkit that lets you turn your AI coding assistant into a team of expert agents. Instead of one general AI, it uses many specialist agents for tasks like coding, security, testing, and DevOps. You just give a task, and OmniRule automatically picks the best agent to handle it.
OmniRule is an open-source, platform-agnostic orchestration layer that transforms AI coding assistants into a coordinated fleet of specialist agents. Instead of relying on a single general-purpose AI, OmniRule dispatches tasks to domain-specific agents — each with curated skills, tools, and operational protocols — ensuring enterprise-grade output quality across architecture, security, testing, DevOps, and more. It works with Claude Code, OpenCode, Codex/GitHub Copilot, Antigravity, Minimax, and any AGENTS.md-compatible runner. Key features include zero-config installation, 190+ pluggable skill modules, built-in security audit, quality gates, and human-in-the-loop approval for dangerous operations. The architecture consists of an Orchestrator agent that classifies tasks and dispatches them to specialist agents, supported by a tools and hooks layer for security, quality, and design extraction.
Looks usable, but maintenance, license, or security notes deserve a closer look.
Last commit was about 29 days ago.
2 GitHub stars indicate community interest.
0 open issues signal maintenance load.
No license detected; review before production use.
Automate complex software development workflows by routing tasks to specialist AI agents for architecture, coding, testing, and deployment.
Enhance code quality and security by automatically running audits and quality gates on every code change.
Accelerate onboarding of new developers by providing a structured set of agents and skills for common tasks.
Integrate with existing CI/CD pipelines to add AI-powered code review and automated refactoring.
Build a multi-agent system for large-scale projects where different agents handle different modules or concerns.
Automated code changes may introduce bugs if not reviewed; always use human-in-the-loop for critical operations.
Security audit tools may produce false positives; manual verification recommended.
Dependency on external AI services may incur costs or have availability issues.
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A best-practices skill for Terraform and OpenTofu AI agents, enabling testing, module structuring, CI/CD, and production infrastructure code.
3 security/trust notes recorded.
Setup difficulty is 2/5.