KPR 是 KPM 软件开发能力的镜像，通过迭代升级跟进，并继续被维护。

让一个代理处理另一个代理的CLI。

一个控制代理可以同时协调多个项目。有了Kaola-Delegator， 每个项目都有自己的托管主机，运行一名项目执行者代理;该执行者 将项目授权的工作人员分配给不同的事务。每个工作人员可以使用 Kaola 工作流程能够自主推进问题，验证结果并反馈。 项目记录和工作树保持在该项目的规范仓库中;工作者 授权不会在项目间合并。

该仓库提供：

• 十一项自成一体的**worker*代理技能——Claude代码、Codex CLI、光标CLI， Devin CLI、Grok CLI、Kimi CLI、OpenCode、ZCode、Droid CLI、dsh（DeepSeek） Harness）和反重力。控制代理在 Git 仓库中启动会话，发送 指令，读取回复和运行时证据，并停止该拥有的 会话。通信仅使用结构化ACP（代理客户端协议）。
• 主控制平面技能 Project Runner（kaola-project-runner）：恢复 授权、计划、调度、心跳、接受后最终确定、自有结账。

Kaola Project Runner

KPR 是 KPM 软件开发能力的镜像，通过迭代升级跟进，并继续被维护。

Let one agent work through another agent’s CLI.

One controlling agent can coordinate multiple projects at once. With Kaola-Delegator, each project gets its own delegated Host running one Project Runner Agent; that Runner assigns the project’s authorized workers to separate issues. Each worker can use Kaola Workflow to autonomously advance its issue, verify the result, and report back. Project records and worktrees stay within that project’s canonical repository; workers and authorization are not pooled across projects.

This repository provides:

• twelve self-contained worker Agent Skills — Claude Code, Codex CLI, Cursor CLI, Devin CLI, Grok CLI, Kimi CLI, OpenCode, ZCode, Droid CLI, dsh (DeepSeek Harness), Antigravity, and Hermes Agent. A controlling agent starts a session in a Git repository, sends instructions, reads replies and runtime evidence, and stops that exact owned session. Communication uses structured ACP (Agent Client Protocol) only.
• the main control-plane Skill Project Runner (kaola-project-runner): recover authorization, plan, dispatch, heartbeat, accept before finalize, own close-out.
• the external Kaola-Delegator Skill (kaola-delegator) for hands-off delegation from an outer Agent.

Pair a chosen entry with Kaola Workflow when that work needs a recoverable path from issue to verified delivery.

Contents

1. Choose an entry — Delegator / Project Runner / Platform Runner / Workflow Next
2. Kaola Workflow integration — normal path, orchestrator binding, evidence-backed exception
3. Install and begin
4. Select workers — runtimes, model selection, worker classes (Expert / Worker / Elite), preset catalog (all 12 runtimes, 28 presets), platform notes
5. Authorization — authorization by class, choosing a worker, seat binding and switching, authorization before a new Host
6. What you specify and what agents own
7. Daily use — session commands, steering, watching ACP sessions
8. For agents
9. Further documentation · Development · License and use

Choose an entry

Pick the most direct entry for how much you want to control. Do not force every task through every layer. Each layer finishes its own job and does not repeat the next.