Harness Engineering

The skillbook for recursive self-improvement (RSI). NVIDIA's latest proof, unpacked with timeless engineering. Distilled from the OpenAI harness engineering hackathon winner's zero-touch method.

Plan, build and review software with your coding agents. Work side by side in the App or browser, or use your favourite terminal or IDE.

A work-centered runtime for agentic software engineering. Work persists; agents, context, and graphs assemble around it.

Official Code for OpenVLHarness: Real-World Visual Agentic Tool‑Use with Multimodal Memory

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

A local multi-agent harness that works with your existing Claude Code, Codex subscriptions, allows you to run an office of agents

My personal directory of skills.

Open survey and evidence map for AI agent evolution, self-evolving agents, memory, skills, harnesses, benchmarks, and agent-swarm systems.

🤖 Official Interactive Tutorial for OpenHarness – Zero to Hero in 12 Chapters | Learn OpenHarness like Claude Code: Agent Loop, Tools, Memory, Multi-Agent | 面向零基础的 AI Agent 交互式教程

Agent harness for codebases. Gives Claude Code, Codex, and CI a shared task system, verdict ledger, and state store so agent work is traceable and auditable.

Open-source AI skill from https://github.com/blogminhquy/javis-os

Learn harness engineering by building Claude Code from scratch. Free, open-source course: 8 articles, 6 videos, 1 codebase.

Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.

Unified Emacs interface supporting OpenAI Codex, Antigravity CLI, Claude Code, Pi agent, Muse Code, and more

Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.

Multi-agent graph orchestration engine for building your own software factory. Bring your own workflow, and the engine enforces it.

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

Harness engineering beginner tutorial, from 0 to 1

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

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

天枢 (Tianshu) 是一个基于harness工程的终端编程智能体运行时（TUI），针对DeepSeek V4 做了前缀缓存工程优化（长会话实测稳态命中率 95–99%）和深度适配。它跳出了传统 AI 编程助手把大模型仅当成“工具”的局限，基于认知虚拟机 (CVM)、自感知层和信息素（Stigmergy）自衰减记忆构建，让 AI 成为有独立判断与认知防护的“开发伙伴”。

天枢harness是一个的终端编程智能体，它要回答的核心问题是：模型何以稳定地交付——目标不漂移、完成有证据、验证有闭环，不说"应该修好了"。为此它在模型与真实世界之间建立一层认知执行环境（CVM），把目标、状态、证据、资源、权限与终止条件从对话历史中外部化，由运行时持续管理。同时对deepseek v4极度优化。

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-tiered permissions, event-sourced replayable sessions, and a fail-closed OS-level sandbox.

Benzi is code intelligence infrastructure for AI models. It compiles your codebase into a resolved, queryable map of calls, data flow, control flow and class hierarchy first; then it reads, explains, runs, edits and verifies your code using it. Every language runs its own tree-sitter grammar into the same query map.