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Agent工作流

AI代理仪表盘

基于 Go · 无代码搭建完整 AI 自动化流程
英文名:agent-dashboard
⭐ 10 Stars 🍴 2 Forks 💻 Go 📄 MIT 🏷 AI 8.0分
8.0AI 综合评分
AI工作流代理管理实时监控
✦ AI Skill Hub 推荐

AI Skill Hub 强烈推荐:AI代理仪表盘 是一款优质的Agent工作流。AI 综合评分 8.0 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。

📚 深度解析
AI代理仪表盘 是一套完整的 AI Agent 自动化工作流方案。随着 AI 能力的不断提升,基于 Agent 的自动化工作流正在成为提升个人和团队效率的核心方式。区别于传统的 RPA 自动化(模拟鼠标键盘操作),AI Agent 工作流通过理解任务意图、动态规划执行路径,能够处理更复杂的非结构化任务。

AI代理仪表盘 工作流的设计遵循"最小配置,最大复用"原则:核心逻辑已经封装好,用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制,在网络波动或 API 限速等情况下仍能稳定运行,适合作为生产环境的自动化基础设施。

在实际部署时,建议先在测试环境中运行 3-5 次,验证各个环节的输出结果符合预期,再部署到生产环境。AI Skill Hub 评分 8.0 分,是同类 Agent 工作流中的精选推荐。
📋 工具概览

AI代理仪表盘 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

GitHub Stars
⭐ 10
开发语言
Go
支持平台
Windows / macOS / Linux(跨平台)
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
8.0 分
工具类型
Agent工作流
Forks
2
📖 中文文档
以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

AI代理仪表盘 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

📌 核心特色
  • 可视化 Agent 工作流编排,无需编写复杂代码
  • 支持多步骤自动化任务链,实现全流程无人值守
  • 与外部 API、数据库和第三方服务无缝集成
  • 内置错误处理与自动重试机制,保障稳定运行
  • 提供可复用的自动化模板,快速在同类场景部署
🎯 主要使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:go install(推荐)
go install github.com/bjornjee/agent-dashboard@latest

# 方式二:从源码编译
git clone https://github.com/bjornjee/agent-dashboard
cd agent-dashboard
go build -o agent-dashboard .

# 方式三:下载预编译二进制
# 访问 Releases 页面下载对应平台二进制文件
# https://github.com/bjornjee/agent-dashboard/releases
📋 安装步骤说明
  1. 访问 GitHub 仓库获取工作流文件
  2. 在对应平台(Dify / Flowise / Make 等)中找到「导入工作流」功能
  3. 上传工作流文件
  4. 按照提示配置必要的环境变量和 API Key
  5. 运行测试确认流程正常后投入使用
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 查看帮助
agent-dashboard --help

# 基本运行
agent-dashboard [options] <input>

# 详细使用说明请查阅文档
# https://github.com/bjornjee/agent-dashboard
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
# agent-dashboard 配置说明
# 查看配置选项
agent-dashboard --config-example > config.yml

# 常见配置项
# output_dir: ./output
# log_level: info
# workers: 4

# 环境变量(覆盖配置文件)
export AGENT_DASHBOARD_CONFIG="/path/to/config.yml"
📑 README 深度解析 真实文档 完整度 90/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

agent-dashboard

A tmux-integrated orchestrator and dispatcher for AI coding agents — Claude Code, Codex, and more.

agent-dashboard runs Claude Code agents across tmux panes, dispatches your input to whichever one needs you, and gates each session through workflow skills (TDD, conventional commits, branch policy) enforced by hooks. The TUI is built with Bubble Tea and styled with Catppuccin Frappe; a companion PWA exposes the same orchestration surface from your phone over your local network.

https://github.com/user-attachments/assets/01aa0f85-cfd4-4dc3-ac46-651bcfc03f99

Both interfaces read agent state from per-agent JSON files in ~/.agent-dashboard/agents/ (written by the Claude Code adapter in adapters/claude-code/ and the Codex adapter in adapters/codex/).

Features

Prerequisites

DependencyRequiredPurpose
[tmux](https://github.com/tmux/tmux)YesAgent pane management and live capture
[Claude Code](https://claude.com/claude-code)YesThe agents this dashboard monitors
[Node.js 18+](https://nodejs.org/)YesClaude Code and Codex adapter hooks
[git](https://git-scm.com/)YesDiff viewer, branch detection
[GitHub CLI (gh)](https://cli.github.com/)NoDetects existing PRs so g opens the diff page instead of creating a new PR
[Codex CLI](https://developers.openai.com/codex/) 0.130+NoShow Codex sessions in the dashboard
[z (zsh plugin)](https://github.com/agkozak/zsh-z)NoFrecency-ranked directory suggestions when creating sessions

Key Dependencies

PackagePurpose
[bubbletea](https://github.com/charmbracelet/bubbletea)TUI framework
[bubbles](https://github.com/charmbracelet/bubbles)Viewport, text input, spinner
[lipgloss](https://github.com/charmbracelet/lipgloss)ANSI styling
[glamour](https://github.com/charmbracelet/glamour)Markdown rendering
[chroma](https://github.com/alecthomas/chroma)Syntax highlighting
[go-gitdiff](https://github.com/bluekeyes/go-gitdiff)Git diff parsing
[toml](https://github.com/BurntSushi/toml)Settings file parsing
[sqlx](https://github.com/jmoiron/sqlx)SQL query helper
[modernc.org/sqlite](https://pkg.go.dev/modernc.org/sqlite)Pure Go SQLite
[fsnotify](https://github.com/fsnotify/fsnotify)File system watcher
[oauth2](https://pkg.go.dev/golang.org/x/oauth2)Google OAuth for mobile web companion

Install

Step 1: Install the binary

Download the pre-built binary from the latest GitHub Release:

curl -fsSL https://raw.githubusercontent.com/bjornjee/agent-dashboard/main/install.sh | sh

The installer downloads the binary for your platform, verifies its SHA256 checksum, and installs it to ~/.local/bin/agent-dashboard. Hooks and skills are delivered through each host's plugin marketplace (see Step 2 and the Codex section below); the installer does not write into ~/.codex. No Go toolchain required.

Or build from source (requires Go 1.26+):

git clone https://github.com/bjornjee/agent-dashboard
cd agent-dashboard
./install.sh --build

Step 2: Register the marketplace and install the plugin

In any Claude Code session, run:

/marketplace add bjornjee/agent-dashboard
/plugin install agent-dashboard@agent-dashboard
/plugin enable agent-dashboard@agent-dashboard

Then restart Claude Code sessions for hooks and skills to take effect.

Uninstall

Usage

Run the dashboard directly:

agent-dashboard

Or if you set up the tmux keybinding, press prefix + D to switch to a dedicated dashboard session.

Optional: tmux keybinding

The included agent-dashboard.tmux script binds prefix + D to switch to a dedicated dashboard session:

```bash

Reload tmux config

tmux source-file ~/.tmux.conf ```

User Settings

The dashboard supports a TOML configuration file at ~/.agent-dashboard/settings.toml (or $AGENT_DASHBOARD_DIR/settings.toml if overridden). From a repo checkout, the installer copies this from settings.example.toml when the destination file does not already exist. Any missing keys fall back to sensible defaults — you only need to include the settings you want to change.

Example settings.toml:

[banner]
show_mascot = true   # show the axolotl pixel art (default: true)
show_quote  = true   # show the daily quote (default: true)

[notifications]
enabled       = false  # enable desktop notifications from adapter hooks (default: false)
sound         = false  # play alert sound on attention events (default: false)
silent_events = false  # show notification for non-alerting stops (default: false)

[debug]
key_log = false       # write key/mouse/focus events to debug-keys.log (default: false)

[experimental]
ascii_pet = false     # show animated ASCII pet in the left panel (default: false)
dino_game = false     # show Chrome-style dino runner game in the left panel (default: false)

[usage]
rate_limit_poll_seconds = 60  # how often to fetch rate limits from Anthropic API (default: 60, 0 = disable)

[effort]
plan    = "high"  # thinking-effort level pinned while permission_mode='plan' (default: high)
default = "high"  # thinking-effort level pinned at spawn and restored on plan exit (default: high)

The [effort] levels feed the /effort slash command Claude Code accepts (low | medium | high | xhigh | max). The agent-state-fast hook swaps in plan when the agent enters plan mode (EnterPlanMode) and restores default on exit. The feature, fix, and refactor skills additionally declare effort: max in their frontmatter, which Claude Code pins for the skill's lifetime when the skill is invoked as a slash command inside an existing session.

SectionKeyDefaultDescription
bannershow_mascottrueShow the axolotl pixel art in the banner
bannershow_quotetrueShow the daily quote in the banner
notificationsenabledfalseEnable desktop notifications from adapter hooks
notificationssoundfalsePlay alert sound on attention events
notificationssilent_eventsfalseShow notification for non-alerting stops
debugkey_logfalseWrite key/mouse/focus events to debug-keys.log
experimentalascii_petfalseShow animated ASCII pet in the left panel
experimentaldino_gamefalseShow Chrome-style dino runner game in the left panel (Shift+G to toggle)
usagerate_limit_poll_seconds60How often (in seconds) to fetch rate-limit data from the Anthropic OAuth API. Set to 0 to disable.
effortplan"high"Thinking-effort level pinned while the agent is in plan mode. One of low, medium, high, xhigh, max.
effortdefault"high"Thinking-effort level pinned at spawn and restored when the agent exits plan mode. Same value set as plan.

Environment Variables

VariableDescriptionRequired
AGENT_DASHBOARD_DIROverride default state directory (~/.agent-dashboard)No
EDITOREditor command for opening agent directories (default: code)No
API_NINJAS_KEYAPI key for quote-of-the-dayNo (falls back to built-in quotes)
GOOGLE_CLIENT_IDGoogle OAuth client ID for mobile companion authenticationNo
GOOGLE_CLIENT_SECRETGoogle OAuth client secretNo
GOOGLE_ALLOWED_EMAILEmail address allowed to access the mobile companionNo

Codex CLI support

Codex support is packaged as a Codex plugin adapter in adapters/codex/. Register the marketplace entry with Codex:

codex plugin marketplace add bjornjee/agent-dashboard

Then enable the plugin by appending the following to ~/.codex/config.toml:

[plugins."agent-dashboard@agent-dashboard"]
enabled = true

Restart Codex sessions and approve the agent-dashboard hooks prompt. Once approved, the dashboard sees Codex sessions just like Claude sessions — same state file, same conversation panel, same cost dashboard. Run codex --model gpt-5.5 in a tmux pane and the agent appears in the dashboard's agent list.

From a repo checkout you can also run make install-codex-adapter, which performs the marketplace registration and prints the config snippet.

Caveats specific to codex:

  • Some skills remain Claude-only. /implement and /rca still rely on Claude-only orchestration primitives. The dashboard returns a 400 for unsupported codex skill combinations.
  • Plan mode is signaled, not gated. Codex's /plan slash command flips the hook payload's permission_mode to "plan". The dashboard captures this as a field but doesn't flip state to plan — codex has no ExitPlanMode equivalent, so there's no discrete "plan ready" review moment.
  • No subagent tree for codex. Codex doesn't have a Task/Agent tool, so the subagent tree panel stays empty for codex sessions.

Step 1: Remove the plugin

In any Claude Code session, run:

/plugin uninstall agent-dashboard@agent-dashboard
/marketplace remove agent-dashboard

FAQ

Do I need tmux? Yes. agent-dashboard reads live pane content via tmux capture-pane and spawns agent sessions in tmux panes. Without tmux there are no panes to monitor.

Which agents are supported? Claude Code is first-class via the adapter in adapters/claude-code/. Codex CLI is supported directly via the adapter in adapters/codex/ (see "How do I see codex agents in the dashboard?" below). Codex is also reachable via skill delegation (/codex-delegate). The architecture supports additional backends via the domain.Harness interface.

How do I use codex / gpt-5.x models? Pick codex in the New Agent harness step (TUI wizard or web form) to spawn the Codex CLI directly, with per-spawn flags from [harness.codex] in ~/.agent-dashboard/settings.toml.

How do I see codex agents in the dashboard? Codex sessions appear once the Codex plugin is installed, enabled, and its hooks approved. Run codex plugin marketplace add bjornjee/agent-dashboard, enable the plugin in ~/.codex/config.toml, restart Codex, and approve the agent-dashboard hooks prompt. See the Codex CLI support section below for details.

Does this require a paid Claude account? No — it uses whatever Claude Code itself requires (Pro, Max, or API). agent-dashboard does not call the Anthropic API directly; it reads the JSONL transcripts Claude Code writes locally.

Can I use the dashboard without the mobile companion? Yes. The TUI is the primary interface. The PWA in cmd/web/ is optional and runs separately via make web.

How is this different from a generic tmux session manager? A session manager creates and switches panes. agent-dashboard understands what's running in each pane — it parses Claude Code's JSONL transcripts to detect state (blocked, waiting, running, done, PR, merged), captures plans and Mermaid diagrams, tracks token usage, and integrates the GitHub PR workflow.

Is this related to Claude Code's official UI? No. agent-dashboard is an unofficial third-party plugin. It builds on top of Claude Code's hooks system and JSONL transcripts but is not affiliated with Anthropic.

Does it work on Windows? Native Windows is unsupported — the project targets macOS and Linux because tmux is required. WSL with tmux installed should work but is untested.

🎯 aiskill88 AI 点评 A 级 2026-05-26

高质量的AI工作流管理工具

⚡ 核心功能
👥 适合人群
自动化工程师和运维人员项目经理和业务分析师希望减少重复性工作的专业人士数字化转型团队
🎯 使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
✅ 优点
  • +MIT 协议,可免费商用
  • +大幅减少重复性人工操作
  • +可视化流程,清晰直观
  • +可扩展性强,支持复杂场景
⚠️ 不足
  • 初始配置和调试需投入一定时间
  • 强依赖外部服务的稳定性
  • 复杂场景需具备一定技术基础
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

🔗 相关工具推荐
🧩 你可能还需要
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❓ 常见问题 FAQ
使用tmux dashboard监控和管理AI编码代理
💡 AI Skill Hub 点评

总体来看,AI代理仪表盘 是一款质量优秀的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 AI代理仪表盘
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 agent-dashboard
原始描述 开源AI工作流:Real-time tmux dashboard to monitor, manage, and orchestrate AI coding agents — 。⭐10 · Go
Topics AI工作流代理管理实时监控
GitHub https://github.com/bjornjee/agent-dashboard
License MIT
语言 Go
🔗 原始来源
🐙 GitHub 仓库  https://github.com/bjornjee/agent-dashboard 🌐 官方网站  https://bjornjee.github.io/agent-dashboard/

收录时间:2026-05-26 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。