#loop-engineering

The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.

Attributed, resolvable artifact references for agent handoffs — a ~30-byte token instead of pasted context. MCP-native; the reference layer for the agent-harness world.

Open-source, self-hostable alternative to Claude Tag — a Slack-style workspace where your team and its AI agents (Claude Code, Codex, GitHub Copilot, and more) work as teammates in channels, threads, DMs, and shared tasks. Your data stays on your machines.

🔁 Build reliable recurring AI-agent systems: 968 resources, 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset.

🤖 An automated setup kit for implementing loop engineering based on issue-driven development in your repository; since 2026.5

Open-source loop engineering for auditable business briefings: claims, evidence, gates, findings, repairs, and human review.

CLI/MCP agent surface for Enji Guard

Hermes Agent starter kit for safe scheduled, stateful AI-agent loops

Human-in-the-loop planning plugin for Claude and Codex: turn ideas into reviewed Markdown plans, record decisions, enforce explicit execution gates, and provide tested controller primitives for safer agent workflows.

A Claude Code skill that turns a mission into a self-maintaining, self-repairing agent harness.

DeepSeek-first local Windows agent for files, research, automation, verified computer use, and auditable office workflows.

Create production-ready agent loops in 30 seconds — scaffolding CLI for Claude Code, Codex, Gemini, and Cursor