Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.

My personal directory of skills.

Enterprise-grade AI Agent Skills for software development, DevOps, SRE, security, and product teams. Compatible with Claude Code, Cursor, Windsurf, Gemini CLI, GitHub Copilot, and 30+ AI coding agents.

Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.

The harness layer for Claude Code — a reference implementation of harness engineering with hook-enforced dual review, state-machine gates that survive context compaction, and fail-closed safety where it counts. Quality gates that AI can't skip.

Professional context and harness engineering for Claude Code and OpenAI Codex. Build production-grade software with spec-driven development, TDD, persistent memory, quality gates, code intelligence, human oversight, and end-to-end verification.

Portable Agent Skill for repository-native Spec programming, informed by public DeepSeek Harness engineering patterns.

📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev

Harness engineering applied to knowledge production: a self-evolving multi-agent newsroom that turns your documents into a cross-linked markdown wiki. A "reground" loop pulls published pages back in before they go stale — writer ≠ reviewer, local-first, a structured alternative to RAG.

A meta-skill that designs domain-specific agent teams, defines specialized agents, and generates the skills they use.

Comet: agent skill harness for turning ideas into evaluated workflows

A kit for building with AI agents and also the engineering patterns around it.

Multi-Agent Harness for Production AI

The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure

DeepBot is a system-level AI assistant built for both personal productivity and enterprise workflows — one-click setup, seamless experience, and native Feishu integration.

Self-hosted agent OS with skills, workflows, MCP, and second brain storage.

Open-source desktop AI agent that gets work done — plans & self-corrects, agentic visual workflows, generative UI, and 100+ offline tools in one self-hostable stack.

A human-governed AI coding workflow that distills ephemeral session context into persistent project memory—making work traceable, reviewable, and resumable.

A Git-native knowledge layer for your team — and a set of tool suite that keeps it alive.

A lightweight agent harness you bolt onto your app so an LLM can operate it — safely, and cheaply.

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

Shared context, memory, and task coordination across AI coding agents. Single Go binary, local SQLite, hybrid keyword and semantic search.

The Loop Engine for Claude Code — engineer the loop, not the prompt. 1 router · 9 agents · 16 skills · 4 workflows. Fail-closed gates, test honesty, anti-anchored review.

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.