#Harness-engineering
Showing 53 of 53 repositories tagged #harness-engineering, ranked by stars
Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
Multi-Agent Harness for Production AI
Harness engineering beginner tutorial, from 0 to 1
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.
🛠️ Awesome tools & guides for harness engineering.
GoClaw - GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy AI agent teams at scale without compromising on safety.
Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.
The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure
Turn any repo into an agent-ready workspace for Claude Code, Codex, Cursor, and other coding agents.
AI workflow automation plugin for intelligent code generation with Claude/Codex
Context drive for your AI agents
KWeaver Core is a harness-first foundation for enterprise decision agents. It turns fragmented data, knowledge, tools, and policies into governed context, safe execution, and verifiable feedback loops. With semantic modeling, real-time access, runtime control, and TraceAI, it helps AI systems reason, adapt, and act reliable in complex enterprises.
What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation.
Open-source agentic data engineering harness for dbt, SQL, and cloud warehouses. 100+ tools, 10 warehouses, AI-powered.
OpenLoomi is a Claude Cowork-style open-source alternative for builders who want local-first work memory around their AI agents
Intelligence that compounds. Every single day.
A general, evolvable, and distributed agent framework & harness for data science.
AI agent tutorials for backend developers without AI background. 适合后端工程师的零基础 AI Agent 教程
Inference-native Tokenmaxxing Agent Harness for Loop Engineering
Veldra — talk an agent into existence, then watch it grow. A self-hostable, local-first agent platform: describe what you need in plain language and it compiles a working agent tools, MCP, RAG, teams. The more you use it, the better it gets agents learn from your feedback and reshape as you talk.
MCP Toolkit for Flutter AI Agent Driven Development (MCP/CLI + custom client side tools) - via closed feedback loop (visual & semantic snapshot) and high client side customization adaptable for any Flutter app. Nowadays it is often called as agentic harness.
Lightweight AI Agent Harness for agentic coding: let strong models explore while humans steer with minimal specs, checkpoints, approval, validation, and reverse sync.
Local-first AI conversation memory hub to capture, search, summarize, and export chats across major AI platforms. 本地优先的 AI 对话记忆与知识中台。
AI-powered QA agent for VS Code. Analyzes code changes, generates test plans, runs real browser tests, and delivers evidence-backed merge verdicts.
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.
A workflow harness that helps AI coding agents plan, review, test, and ship safer code.
One person, one software company. Manage 47 AI agents from a single Electron app — with Harness Engineering (Skills + Hooks + FileWatchers) for disciplined, traceable AI workflows.
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.
Open survey and evidence map for AI agent evolution, self-evolving agents, memory, skills, harnesses, benchmarks, and agent-swarm systems.
🐴 Prompt-first harness engineering for safer AI coding agent workflows.
The Map Everyone's Missing: LLM Knowledge Engineering in 2026 — First unified guide connecting RAG, Context Engineering, Harness Engineering, Skill Systems, Agent Memory, MCP, and Progressive Disclosure
Dryforge : New generation of harness engineering - Claude Code & Codex Plugin.
The first AI plugin that speaks first. Code-enforced learning + active forgetting + PAC (Proactive Accountability Challenge). Works with Claude Code, Gemini CLI, Hermes, OpenClaw.
Mexus is a local web console for managing multiple CLI AI Agent instances in parallel.
智能体 = 大模型 + Harness。深入剖析 Harness 工程原理、设计、实现与实践！
BizDevOps rhythm manager for Claude Code — trace business goals to code changes with 18 skills
Context engineering for coding agents - CLAUDE.md templates, mechanical enforcement, and a field guide to 20+ best practices. Bootstrap with one command.
The Python Harness for Production AI Multi-Agent Systems
Open-source Environment toolkit of claw-like agents, support task/harness generation and evaluation
The linter for your agent harness. Works with Claude Code, Codex, and Cursor.
Harness Engineering Practice: PRD Driven Development Framework
AI Harness Engineering Template — guardrails, gates, and boundaries for AI coding agents. One-command install. Zero dependencies.
A structured workflow system for AI coding agents - harness engineering, execution loop, skills, hooks, and a learning loop. Works with Claude Code, Codex, Antigravity CLI, Copilot.
基于 FastAPI 的生产级 AI Agent 框架，支持 100+ LLM 提供商、MCP 工具集成、多 Agent 协作、RAG 知识库和沙箱隔离执行
Claude Code scaffolding and first steps for complex brownfield projects
给你的 Agent 配个「纪律委员」—— 约束工作习惯（先读后写/验证再干/谨慎修改），从错误中沉淀教训；核心层纯 bash 零依赖，编排引擎可选，OpenClaw first。
🤖 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
A production-grade multi-platform monorepo demonstrating shared business logic across Web and Mobile. Showcases engineering practices, decision-making and AI-assisted optimization for senior full-stack
《智能体工程：从一句话到一个闭环》（Prompt · Context · Harness · Loop），本书将大语言模型驱动的智能体系统拆解为四种递进的工程范式，四种范式从 Token 到 System，从一次调用到完整的自主闭环，构成了智能体系统的完整工程视图。
A production-grade Kanban board application. Showcases engineering practices, decision-making and AI-assisted optimization for senior full-stack roles.
A small, file-first verification harness that turns an AI agent's "I'm done" claim into an auditable admission decision. 100% offline & zero-infra
Evaluate and optimize your AI agent context. Save tokens, save money.