Multi-agent harness that runs Claude Code and Codex together as one system

Multi-Agent Harness for Production AI

a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task

Turn any repo into an agent-ready workspace for Claude Code, Codex, Cursor, and other coding agents.

Prior direction, kept rather than deleted. Signed, offline-verifiable receipts for AI agent actions, and a reference implementation of the OWASP Agentic Skills Top 10 AST09 receipt pattern. Nobulex is now the independent reliability registry for agent tools: github.com/arian-gogani/nobulex-registry

Agent Skill that analyzes your repo and generates the AI-ready configuration coding agents need — AGENTS.md, copilot-instructions, CI, issue templates, and more. Works in Claude Code, GitHub Copilot, Codex, and Cursor.

Turn tracker tickets into autonomous agent sessions

Visible multi-agent CLI workspace for mixing Codex, Claude, Gemini, Kimi, Qwen, Cursor, Copilot, Pi, OpenCode, and other AI coding agents

Minimal AI coding agent (~1,000 lines of Python) inspired by Claude Code. Works with any LLM. Think NanoGPT for coding agents. Formerly NanoCoder.

Use cultivar to test your Agent Skills, run them in sandboxes, and across different agents.

Independently authored prompt templates for AI coding agents — system prompts, tool prompts, agent delegation, memory management, and multi-agent coordination. Informed by studying Claude Code.

Bring Claude Code, Codex, and your favorite CLI agents into one visual workspace. Run agents in parallel and build executable workflows in isolated Git worktrees. Build your own AI coding team, and turn builds, tests, and dev servers into reusable canvas workflows.

Touhou-inspired Agent Skills: distinct, testable, composable problem-solving workflows.

A native Python agent CLI built on DeepAgents CLI, featuring an independent memory Agent that captures learnings after each task and delivers efficient AI coding assistance through hierarchical memory management.

Production-grade Agent Skills for AI coding agents—composable workflows for planning, TDD, debugging, review, UI/UX, releases, incidents, and evals.

Composable agent runtime with enforced isolation boundaries

The IM for agents. Shared Agent Context & Memory, supervised execution, and cross-agent audit across AI providers.

Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as a daemon.

An evaluation and evolution tool for Agent Skills.

Open-Source Platform for Subagents and Agent Teams. Long-running, collaborative, proactive.

Orchestrate AI coding agents (Claude Code, Codex) as parallel subagents over tmux — a loop-engineering runtime with auto-continue, execute-then-review, and cross-session memory.

Emdash is the Open-Source Agentic Development Environment (🧡 YC W26). Run multiple coding agents in parallel. Use any provider.

OpenCode plugin: Ralph outer loop + RLM inner loop — iterative AI development with file-first discipline and sub-agent support

Open-source AI agent harness in native Rust — GUI, CLI, headless, and webapp from one binary. Multi-provider, MCP, skills, plugins, agent teams.