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Agent Skill · 效率

codex-autopilot(Codex autopilot 自动化)

codex-autopilot 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

codex-autopilot 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 4,024。

总安装 14,660周安装 617GitHub Stars 公开资料未说明下载 5,133核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.7.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:codex-autopilot(Codex autopilot 自动化)
来源仓库:https://github.com/imwyvern/codex-autopilot
安装命令:
openclaw skills install codex-autopilot
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install codex-autopilot

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

codex-autopilot 用于多模型 AI 编码自动化系统。协调 Codex 和 Gemini 模型完成前后端开发任务。通过 clawhub 安装,需确认是否会触发外部 API 调用。内置 CI/CD 管道,适合自动化部署和测试流程。建议设置看门狗机制以防止无限循环执行。

codex-autopilot 属于效率类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install codex-autopilot;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

codex-autopilot 怎么安装?

在终端执行 openclaw skills install codex-autopilot。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codex-autopilot 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

codex-autopilot 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

codex-autopilot 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

codex-autopilot 用的人多吗?

公开数据是累计安装 14,660 次,近一周安装 617 次,下载 5,133 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

codex-autopilot 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
codex-autopilot

Codex autopilot 自动化 · 本页

14,660—需要联网MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
codex-autopilot
version
0.7.1
description
|
Triggers
autopilot, watchdog, codex automation, tmux codex, multi-project codex, auto-nudge codex, codex session management, gemini frontend, multi-model routing, ai task routing, ci cd, test agent, coverage ratchet.

Codex Autopilot

Multi-model AI coding orchestration via tmux + launchd on macOS.

Overview

Codex Autopilot runs a watchdog loop that orchestrates multiple AI coding sessions in tmux. It features intelligent task routing — frontend tasks (UI, components, H5) are routed to Gemini CLI (1M context window, superior design aesthetics), while backend tasks (API, database, deployment) go to Codex CLI. The watchdog detects idle sessions, auto-nudges them, handles permission prompts, dispatches tasks from a priority queue, and sends notifications via Discord/Telegram.

Multi-Model Architecture

RoleModelStrengths
Backend codingCodex (GPT-5.4)API, database, deployment, refactoring
Frontend developmentGemini CLIUI, components, pages, styles, 1M context
OrchestrationClaude / OpenClawTask routing, code review, project management

Tasks are automatically classified by keywords and routed to the appropriate model. Frontend tasks fall back to Codex if Gemini is unavailable.

Installation

git clone https://github.com/imwyvern/AIWorkFlowSkill.git ~/.autopilot
cd ~/.autopilot
cp config.yaml.example config.yaml
# Edit config.yaml with your project paths, Telegram bot token, and Discord channels

Dependencies

  • macOS with launchd (for scheduled execution)
  • tmux — session multiplexer for Codex windows
  • Codex CLI (codex) — OpenAI's coding agent
  • python3 — for state cleanup and PRD verification scripts
  • yq — YAML processor for config parsing
  • jq — JSON processor for state management
  • bash 4+ — for associative arrays in scripts

Install dependencies via Homebrew:

brew install tmux yq jq

launchd Setup

Use install.sh to register the launchd plist:

./install.sh

This creates a LaunchAgent that runs the watchdog on a configurable interval.

Core Components

watchdog.sh

Main loop engine. On each tick:

  1. Iterates through configured project tmux windows
  2. Captures current Codex output via codex-status.sh
  3. Determines if session is active, idle, or stuck
  4. Dispatches appropriate action (nudge, permission grant, task from queue)
  5. Enforces cooldowns, daily send limits, and loop detection

codex-status.sh

Captures and analyzes tmux pane content. Detects:

  • Codex activity state (working / idle / waiting for permission)
  • Permission prompts requiring approval
  • Context compaction signals
  • Error states and crashes

tmux-send.sh

Sends keystrokes or text to a specific tmux window. Handles:

  • Typing text into Codex prompt
  • Pressing Enter/keys for permission approval
  • Verification polling to confirm send succeeded

autopilot-lib.sh

Shared function library used by all scripts:

  • Telegram notification helpers
  • File locking primitives
  • Timeout and retry logic
  • Logging utilities
  • State file read/write

autopilot-constants.sh

Defines status constants used across scripts (e.g., STATUS_ACTIVE, STATUS_IDLE, STATUS_PERMISSION).

task-queue.sh

Task queue manager. Supports:

  • Enqueuing tasks for specific projects
  • Dequeueing next task based on priority
  • Task status tracking (pending/running/done/failed)

discord-notify.sh

Sends formatted notifications to Discord channels via webhook. Supports project-channel routing defined in config.yaml.

test-agent.sh

Built-in CI/CD that runs on every commit. Evaluates test suites, tracks coverage, and auto-enqueues bugfix tasks when tests fail.

commit → watchdog detects → test-agent evaluate
  ├─ all pass → review clean → enqueue coverage tasks for low-coverage files
  └─ failures → parse log → auto-enqueue "fix(test): ..." bugfix task
       └─ 1h cooldown per file (prevents retry loops)

Triggers:

  • on_commit_evaluate — every new commit
  • on_review_clean — after code review passes
  • nightly — scheduled full evaluation (default 02:30)

Coverage ratchet: global coverage must not regress; weekly +1% target, capped at 90%.

Other Scripts

ScriptPurpose
auto-nudge.shNudge logic for idle Codex sessions
auto-check.shPeriodic health check across all projects
permission-guard.shAuto-approve or flag permission prompts
incremental-review.shRun code review on recent changes
monitor-all.shDashboard: show status of all monitored projects
status-sync.shSync state to status.json for external consumption
rotate-logs.shLog rotation and cleanup
cleanup-state.pyRemove stale entries from state.json
claude-fallback.shFallback handler when Codex is unavailable
prd-audit.shAudit PRD completion status
prd-verify.sh / prd_verify_engine.pyVerify PRD items against codebase
codex-token-daily.pyTrack daily token usage
coverage-collect.shCollect and merge coverage reports

Configuration

Edit config.yaml (copy from config.yaml.example). Key sections:

Timing Thresholds

active_threshold: 120    # seconds — Codex considered "working"
idle_threshold: 360      # seconds — Codex considered "idle", triggers nudge
cooldown: 120            # minimum seconds between sends to same project

Safety Limits

max_daily_sends_total: 200   # global daily send cap
max_daily_sends: 50          # per-project daily cap
max_consecutive_failures: 5  # pause project after N failures
loop_detection_threshold: 3  # detect repeated output loops

Multi-Project Scheduler

scheduler:
  strategy: "round-robin"    # or "priority"
  max_sends_per_tick: 1
  inter_project_delay: 5     # seconds between project sends

Project Directories

project_dirs:
  - "~/project-alpha"
  - "~/project-beta"

Gemini Frontend Routing

gemini:
  default_window: "gemini-h5"        # Default tmux window for frontend tasks
  project_windows:
    youxin: "gemini-youxin"          # Per-project Gemini window overrides

Frontend task detection keywords: 页面, 组件, 样式, UI, 前端, H5, 小程序, 界面, frontend, component, style, page, layout

Discord Channel Routing

discord_channels:
  my-project:
    channel_id: "123456789"
    tmux_window: "my-project"
    project_dir: "/path/to/project"

Telegram Notifications

telegram:
  bot_token: "YOUR_BOT_TOKEN"
  chat_id: "YOUR_CHAT_ID"
  status_interval: 1800

Usage

Adding a Project

  1. Start a Codex CLI session in a named tmux window:
   tmux new-window -t autopilot -n my-project
   # In the new window, cd to project and run codex
  1. Add the project path to config.yaml under project_dirs
  1. Optionally create projects/my-project/tasks.yaml for task queue:
   project:
     name: "My Project"
     dir: "~/my-project"
     enabled: true
     priority: 1
   tasks:
     - id: "feature-x"
       name: "Implement feature X"
       prompt: |
         Implement feature X per the spec in docs/feature-x.md

Manual Operations

# Check status of all projects
./scripts/monitor-all.sh

# Manually nudge a specific project
./scripts/auto-nudge.sh my-project

# Send a command to a tmux window
./scripts/tmux-send.sh my-project "codex exec 'fix the tests'"

# Enqueue a backend task (routes to Codex)
./scripts/task-queue.sh add my-project "Refactor auth module"

# Enqueue a frontend task (routes to Gemini)
./scripts/task-queue.sh add my-project "重构登录页面组件" normal --type frontend

# Run the watchdog once (for testing)
./scripts/watchdog.sh

Python Autopilot (Alternative)

autopilot.py provides a Python-based alternative with richer state management:

python3 autopilot.py --once        # single pass
python3 autopilot.py --daemon      # continuous loop

Directory Structure

~/.autopilot/
├── SKILL.md                 # This file
├── config.yaml              # Local config (not in git)
├── config.yaml.example      # Config template
├── scripts/                 # All automation scripts
├── projects/                # Per-project task definitions
├── docs/                    # Additional documentation
├── code-review/             # Code review templates
├── development/             # Development workflow templates
├── doc-review/              # Doc review templates
├── doc-writing/             # Doc writing templates
├── requirement-discovery/   # Requirement discovery templates
├── testing/                 # Testing templates
├── tests/                   # Test suite
├── state/                   # Runtime state (gitignored)
├── logs/                    # Runtime logs (gitignored)
├── task-queue/              # Task queue data (gitignored)
└── archive/                 # Deprecated files

平台分布

OpenClaw

75.54%
按下载量换算3,877

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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