Better Harness Blog

最近，我们一直在尝试优化 Better Harness 的 SKILL 自动沉淀能力：从 Agent 的真实会话中识别重复出现的工作路径，再判断其中哪些经验值得进一步沉淀成可复用的 SKILL。真正做起来以后，我们发现这件事远比“把一段 Session 分析一遍”复杂得多。

对于一次软件开发任务来说，Agent 的行为并不是孤立发生的。它从一个需求或者用户故事开始，经过对需求的理解、上下文探索、代码修改和验证，最终才形成一次可以被评审的代码贡献。只看中间的 Session，我们能看到 Agent 做了什么，却很难判断这些行为为什么发生，又有哪些行为真正进入了最后的交付。

因此，我们开始把一次 Agent 的交付理解成一条连续的链路。现在，只需要在项目目录执行：

npx @qoder-ai/better-harness inspector

就可以生成一个本地、只读的 Harness Inspector 页面，把当前项目中的 Agent Session、文件活动和 Git Commit 放到同一个交互界面里。

Writing a capability into a SKILL.md and packaging it as an Agent plugin is not hard. The hard part comes later: once that capability is invoked over and over by different users, in different projects, and on different Agent hosts, how do you guarantee that it is still triggered, executed, and verified correctly? And how do you prove that a change made it better rather than worse?

Drawing on how Better Harness is actually developed, this post walks through five engineering practices - spec-driven behavior, context orchestration, deterministic verification, behavioral evaluation, and the evidence loop - that move a plugin capability from "it works when I run it" to a software asset that is verifiable, maintainable, and safe to evolve.

Last week, we built Better Harness into Qoder Desktop. After launch, many users asked the same question: Will this be open source?

In its first three days, 100,000 people tried Better Harness.

The answer is yes.

Today, Better Harness is officially open source. You can find the project at github.com/QoderAI/better-harness.

Better Harness is an open-source analysis and continuous-improvement tool for coding-agent workflows. It connects the engineering practices, evaluation model, and runtime capabilities of Harness Engineering and Loop Engineering. The initial open-source release supported Claude Code, Codex, Qoder, and Cursor with one shared judgment model, although session analysis, evidence coverage, and output capabilities were not yet identical across the four hosts. Qoder, which had already been exercised repeatedly in real development workflows, was the most complete reference implementation at launch.

Today's coding agents can read requirements, modify code, run tests, and even submit pull requests. But being able to do many things is not the same as being able to do them well.

An agent usually cycles through understanding the task, taking action, checking the result, and adjusting its next step. That is the Agent Loop. A reliable loop does more than keep the agent moving: it gives the agent a clear goal, defines what it must not touch, explains how to judge the result, and provides a recovery path when something fails. Without those boundaries, an agent may change a great deal of code and run many tests while still being unable to prove that the task is actually complete.

This is the problem that Loop Engineering and Harness Engineering address. They equip the agent with project context, relevant development tools, effective verification methods, and explicit safety boundaries so that every loop moves closer to a reliable delivery.

Building on Qoder's internal experience and the broader community's work on coding agents, agent loops, and software engineering, we introduced Better Harness (Beta).