loop-engineering README

The project's README from github.com/cobusgreyling/loop-engineering. As one markdown file: README.md.

Loop Engineering

Showcase GitHub stars loop npm last triage MIT

Loop Engineering logo

Stop prompting. Design the loop. Get a score.

Loop Engineering — design the system that prompts your agents

Start in 5 minutes · Quickstart · What do you want to do? · Refactor path · 中文 · Pattern picker

npx @cobusgreyling/loop init . --pattern daily-triage --tool claude
npx @cobusgreyling/loop doctor .

--tool defaults to claude if you omit it. Swap for grok, codex, or opencode. Week one is report-only.

Loop Ready score climbing

You design a system that discovers work, hands it to agents, verifies results, and persists state — instead of typing the next prompt yourself.

New here? Quickstart · Refactor a project · Thin GitHub Action loop (no STATE.md required)

What do you want to do?

This is a pattern library for operating agents around a codebase. It is not a “rewrite the module” button.

I want to… Start here
Keep the repo healthy (issues, CI, deps) Quickstart → daily-triage
Land and babysit PRs PR Babysitter
Run a loop in GitHub Actions with almost no files Thin loop
Ship a feature or refactor (todos → small PRs) Refactor / change path

Full jobs table: docs/jobs.md.

Patterns

Pattern Cadence Week 1 Cost
Daily Triage 1d–2h L1 report Low
Thin loop event + 1d L1 snapshot Very low
PR Babysitter 5–15m L1 watch High
CI Sweeper 5–15m L2 cautious Very high
Dependency Sweeper 6h–1d L2 patch-only Medium
Changelog Drafter 1d or tag L1 draft Low
Post-Merge Cleanup 1d–6h L1 off-peak Low
Issue Triage 2h–1d L1 propose-only Low

Interactive picker: showcase. Index: patterns/registry.yaml.

Getting started

npx @cobusgreyling/loop init . --pattern daily-triage --tool claude
npx @cobusgreyling/loop doctor .
npx @cobusgreyling/loop cost --pattern daily-triage --level L1

Empty repo → first STATE.md walkthrough: scripts/empty-to-state-demo.sh.

Roll out L1 report → L2 assisted → L3 unattended only after the verifier has been right for a week. See loop-design-checklist.

Loop Ready now weights recent runs harder than files on disk. A 30-day-old STATE.md is not L3.

Examples by tool

Claude Code (including the plugin) · Grok · Codex · OpenClaw · Opencode · GitHub Actions

Operating & safety

Failure modes · Anti-patterns · Safety · Operating loops · Stories (wins and failures)

Loop engineering amplifies judgment. Token costs can explode. Unattended loops make unattended mistakes. Read what the loop ships.

Help wanted

Docs and small PRs: first response within 48 hours.

See CONTRIBUTING.md.

CLI packages and companion repos (optional — not required for week one)

Unified front door: npx @cobusgreyling/loop (init · doctor · status · audit · cost). Older packages (loop-init, loop-audit, …) stay supported.

Companions exist for later: memory-engineering, harness-foundry, outerloop, fleet-engineering, goal-engineering. Do not add them until a loop has actually run.

Sources

License

MIT

loop-engineering (cobusgreyling/loop-engineering)

Searching Database…

这是什么?Loop Engineering 是一套模式库和一组命令行工具,用于设计自动化循环:AI 编程智能体在循环中自行发现任务、执行任务、验证结果,并把状态保存在仓库里,而不需要你亲自输入下一条提示词。
这是一个框架,还是只是一些命令行工具?它主要是一个有文档说明的模式库(如 Daily Triage、PR Babysitter、CI Sweeper 等),外加配套的命令行工具 loop-audit、loop-init、loop-cost,以及实现这些模式的 GitHub Actions 模板。它不是一键式的代码改写工具。
它支持哪些编程智能体?示例和 --tool 参数涵盖 Claude Code(包括一个插件)、Grok、Codex、OpenClaw 和 Opencode;如果不指定,默认使用 Claude。
它开箱即用就能让我的智能体完全无人值守地运行吗?不能。它应该逐级推广:先从 L1(仅报告)到 L2(辅助),再到 L3(无人值守),而且只有在验证器被证明判断正确满一周之后,才能进入 L3。一个旧的 STATE.md 文件不能算作已经准备好进入 L3。
这个库包含哪些模式?共有八个有文档说明的任务,覆盖常见的仓库维护工作:Daily Triage、Thin loop、PR Babysitter、CI Sweeper、Dependency Sweeper、Changelog Drafter、Post-Merge Cleanup 和 Issue Triage。每个任务都附有建议的运行频率、起始安全级别和大致成本。
项目自带哪些命令行工具?较早的独立工具 loop-init、loop-audit、loop-cost、loop-sync、loop-context 和 loop-gate 仍然受支持,现已统一到单个 npx @cobusgreyling/loop 命令之下。
为什么要创建 Loop Engineering?它把围绕 AI 编程智能体设计系统、而不是编写一次性提示词这一理念系统化了,借鉴了 Addy Osmani 和 Boris Cherny 的观点,并在一篇 2026 年关于智能体循环采纳情况的学术论文中,被引用为社区的参考实现。
运行这些循环最大的风险是什么?README 警告说,Loop Engineering 会放大你的判断,好的判断和坏的判断都会被放大,因此 token 成本可能失控,而无人值守的循环也可能犯下无人值守的错误。你需要真正阅读循环交付的内容。
Size
6.3 MB
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Age
4mo
Commits · 90 Days