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开源AI工作流
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Agent工作流

开源AI工作流

基于 Shell · 无代码搭建完整 AI 自动化流程
英文名:openclaw-revenium
⭐ 11 Stars 💻 Shell 📄 未公布协议 🏷 AI 7.5分
7.5AI 综合评分
AI工作流预算执行
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,开源AI工作流 获评「推荐使用」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。

📚 深度解析

开源AI工作流 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。

开源AI工作流 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 7.5 分,是同类 Agent 工作流中的精选推荐。

📋 工具概览

开源AI工作流 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
⭐ 11
开发语言
Shell
支持平台
macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
未公布
AI 综合评分
7.5 分
工具类型
Agent工作流
Forks

📖 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」。

开源AI工作流 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
# 克隆仓库
git clone https://github.com/revenium/openclaw-revenium
cd openclaw-revenium

# 查看安装说明
cat README.md

# 按 README 完成环境依赖安装后即可使用
📋 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
openclaw-revenium --help

# 基本运行
openclaw-revenium [options] <input>

# 详细使用说明请查阅文档
# https://github.com/revenium/openclaw-revenium
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
# openclaw-revenium 配置说明
# 查看配置选项
openclaw-revenium --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 OPENCLAW_REVENIUM_CONFIG="/path/to/config.yml"
📑 README 深度解析 真实文档 完整度 58/100 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。

Revenium OpenClaw Skill

Budget enforcement and token metering for OpenClaw agents using the Revenium platform. Tracks AI spend, enforces configurable Revenium guardrail rules, and reports usage automatically — so agents never silently blow through your token budget.

🛡️ Running OpenClaw under NemoClaw / OpenShell? This README covers the standalone OpenClaw + Docker path. For the parallel NemoClaw/OpenShell sandbox install path, follow docs/nemoclaw-setup.md instead.

Prerequisites

  brew install revenium/tap/revenium
  

The skill is gated on this binary and won't load without it. (post-install.sh also installs it automatically via Homebrew if it's missing — see step 2.) - Revenium API key, Team ID, Tenant ID, and Owner ID

Installation

1. Install the skill from ClawHub

clawhub install --force --dir ~/.openclaw/skills revenium
About the VirusTotal warning: ClawHub may display a warning that this skill is "flagged as suspicious by VirusTotal Code Insight." This is a false positive — the skill calls the Revenium API via the revenium CLI and handles API keys during setup, which triggers VirusTotal's heuristic detection for "external APIs" and "crypto keys." The skill is open source and safe to install. The --force flag bypasses this warning.
Installing for local development or testing from this Git repo instead of ClawHub? See Installing from the GitHub repo below.

2. Run post-install setup

ClawHub does not run post-install scripts, so run the setup script first — it installs any missing prerequisites (including the revenium CLI itself, which the next step needs) and configures OpenClaw sandbox access:

bash ~/.openclaw/skills/revenium/scripts/post-install.sh

This will:

1. Check for and install the revenium CLI and jq via Homebrew (if missing), and verify python3 is available 2. Mark the skill's scripts as executable 3. Configure the Docker sandbox under agents.defaults.sandbox.docker in ~/.openclaw/openclaw.json: - Bind-mounts ~/.openclaw (rw — skills, sessions, logs, guardrail-status.json) and the Homebrew bin/lib directories containing revenium and jq (ro) - Sets PATH, HOME, LD_LIBRARY_PATH, and SSL_CERT_FILE in the container environment - Injects REVENIUM_API_KEY / REVENIUM_API_URL / REVENIUM_TEAM_ID / REVENIUM_TENANT_ID / REVENIUM_OWNER_ID from your host config (so the CLI inside the sandbox is authenticated without mounting ~/.config) - Sets dangerouslyAllowExternalBindSources: true — required so the gateway accepts the ~/.openclaw and Homebrew binds, which live outside the sandbox's default ~/.openclaw/workspace root. It does not mount any credential path; those remain hard-blocked by OpenClaw regardless of this flag. 4. Enable autoAllowSkills in ~/.openclaw/exec-approvals.json so skill-declared binaries are auto-approved 5. Seed an initial guardrail-status.json so the agent doesn't error before the cron's first run 6. Seed an initial config.json (prompts interactively for autonomousMode) so operators can set the halt-vs-warn behavior up front 7. Inject a mandatory guardrail check into AGENTS.md so enforcement is always in context 8. Deploy BUDGET-GUARD.md into the workspace so enforcement is injected into isolated/cron sessions too 9. Verify the installation

On this first run your Revenium credentials aren't set yet, so post-install will warn that it couldn't inject them into the sandbox — that's expected. You'll set them and re-run post-install in step 3.
Already have prerequisites installed? Pass --skip-prereqs to skip Homebrew installs and fail immediately if anything is missing.

3. Set Revenium credentials on the host, then re-run post-install

Now that the revenium CLI is installed (step 2), set your credentials on the host and re-run post-install so they get injected into the sandbox:

revenium config set key <API_KEY>
revenium config set team-id <TEAM_ID>
revenium config set tenant-id <TENANT_ID>
revenium config set owner-id <OWNER_ID>
revenium config show          # confirm the values are set

bash ~/.openclaw/skills/revenium/scripts/post-install.sh   # re-run to snapshot creds into the sandbox

The revenium CLI stores these at ~/.config/revenium/config.yaml.

Credentials reach the sandbox as a snapshot, not live. OpenClaw's sandbox hard-blocks mounting credential paths (anything under ~/.config), so the skill cannot bind-mount your revenium config into the container. Instead, post-install reads your host credentials and injects them as REVENIUM_* environment variables into the sandbox. This means any time you set or rotate credentials, you must re-run post-install and restart the gateway (steps 3–4) to refresh them. Setting revenium config set from inside an agent session has no effect on the sandbox.

First-time setup (automatic)

The metering cron and guardrail rules are configured the first time you interact with the agent after installing the skill. The agent walks you through configuring your budget and creates the guardrail rules — no manual script execution needed.

To verify the cron is running after setup:

tail -f ~/.openclaw/skills/revenium/revenium-metering.log

To manually manage the cron:

```bash

Reinstall

bash ~/.openclaw/skills/revenium/scripts/install-cron.sh

Uninstall

bash ~/.openclaw/skills/revenium/scripts/uninstall-cron.sh ```

Installing from the GitHub repo (local development)

Use this when you want to run or test unreleased changes (e.g. a feature branch) instead of the ClawHub release. The key constraints, both enforced by OpenClaw's sandbox:

  • The skill must be a real directory inside ~/.openclaw/skills/do not symlink a clone from elsewhere. OpenClaw rejects skills whose path resolves outside the skills root (reason=symlink-escape).
  • Credentials are injected into the sandbox as a snapshot at post-install time. Because post-install is also what installs the revenium CLI, the order is: run post-install once (installs the CLI) → revenium config set … → re-run post-install to snapshot the creds. Re-run post-install after any later credential change too.

2. Run post-install, set credentials, re-run post-install, restart

```bash

Run post-install FIRST — it installs the `revenium` CLI (and jq) if missing.

...and re-run post-install to snapshot them into the sandbox, then restart.

bash ~/.openclaw/skills/revenium/scripts/post-install.sh openclaw gateway restart ```

Re-run post-install ONLY if the sandbox config, credentials, or AGENTS.md

Setup

Setup happens automatically the first time the agent tries to perform an operation (or run /revenium to start it manually). The agent will:

  1. Confirm your Revenium API key, Team ID, Tenant ID, and Owner ID are visible in the sandbox (set on the host, per step 3)
  2. Ask for a budget threshold (e.g., 5.00)
  3. Ask for a budget period (DAILY, WEEKLY, MONTHLY, or QUARTERLY)
  4. Optionally enable shadow mode (record breaches without enforcing) and autonomous mode (halt-on-exceed with notifications to Slack, Discord, Telegram, etc.)
  5. Create the Revenium guardrail rules and save their ruleIds to ~/.openclaw/skills/revenium/config.json
  6. Install the background metering cron (runs every minute by default; configurable)

Setup is atomic — if rule creation fails, no partial ruleIds are written.

Setup is idempotent. Re-running setup (or installing on a fresh VM pointed at the same Revenium tenant) checks for an existing same-scope budget rule before creating a new one. If a match is found, setup adopts the existing rule rather than creating a duplicate. If multiple same-scope rules are detected (e.g., from earlier redundant runs), setup warns and prints the exact revenium guardrails budget-rules delete <id> --yes command for each — it does not auto-delete, since a shared tenant may host rules belonging to other hosts.

Rule names include a deployment label suffix (e.g., OpenClaw Monthly Budget — my-host). Override the label via the REVENIUM_BUDGET_LABEL env var before invoking setup-guardrails.sh to produce human-distinguishable names when multiple hosts share the same Revenium tenant. Default: short hostname from hostname -s.

Per-deployment budget scoping (independent filter-scoped budget rules per deployment, rather than a single shared tenant budget) is a separate future capability and is currently out of scope.

Or persist it in config.json so future re-installs pick it up:

Uninstalling

bash ~/.openclaw/skills/revenium/scripts/uninstall-cron.sh
rm -rf ~/.openclaw/skills/revenium

Optionally clean up your Revenium guardrail rules:

revenium guardrails budget-rules list
revenium guardrails budget-rules delete <rule-id> --yes

Configuration

The skill stores its config at ~/.openclaw/skills/revenium/config.json:

{
  "ruleIds": ["d5jng5"],
  "organizationName": "my-org",
  "autonomousMode": false,
  "notifyChannel": "slack",
  "notifyTarget": "#ops",
  "cronIntervalMinutes": 1
}
  • ruleIds — the Revenium guardrail rule IDs (created during setup; their presence is the signal that setup is complete)
  • organizationName — optional, used for attribution in Revenium reporting
  • autonomousMode — when true, budget exceedance halts all operations and sends notifications; when false (default), the agent warns and asks for permission
  • notifyChannel / notifyTarget — notification destination for autonomous-mode halt alerts
  • cronIntervalMinutes — optional, how often the metering/guardrail cron runs (default 1); see Cron interval

Your API key, Team ID, Tenant ID, and Owner ID are stored separately by the revenium CLI (at ~/.config/revenium/config.yaml) and injected into the sandbox as REVENIUM_* environment variables by post-install.

Now that the CLI exists, set Revenium credentials on the host...

revenium config set key <API_KEY> revenium config set team-id <TEAM_ID> revenium config set tenant-id <TENANT_ID> revenium config set owner-id <OWNER_ID>

Troubleshooting

📚 实用指南(长尾问题)
适合谁
  • 需要 openclaw-revenium 解决具体问题的开发者与运营人员
最佳实践
  • 先在测试环境跑通最小用例,再接入生产数据
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
部署方案
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
openclaw-revenium 中文教程openclaw-revenium 安装报错怎么办openclaw-revenium 与同类工具对比openclaw-revenium 最佳实践openclaw-revenium 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要 openclaw-revenium 解决具体问题的开发者与运营人员
⭐ 最佳实践
  • 先在测试环境跑通最小用例,再接入生产数据
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)

👥 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
  • +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
  • 未明确开源协议,商用场景需谨慎评估
  • 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

该工具未明确声明开源协议,商业使用前请联系原作者确认授权范围,避免侵权风险。

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。

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❓ 常见问题 FAQ

参考README文档
💡 AI Skill Hub 点评

AI Skill Hub 点评:开源AI工作流 的核心功能完整,质量良好。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。

⬇️ 获取与下载
⚠️ 该工具未声明开源协议,不提供直接下载。请访问原项目了解使用条款。
📚 深入学习 开源AI工作流
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🌐 原始信息
原始名称 openclaw-revenium
原始描述 开源AI工作流:Budget enforcement and token metering skill for OpenClaw agents. Tracks AI spend。⭐11 · Shell
Topics AI工作流预算执行
GitHub https://github.com/revenium/openclaw-revenium
语言 Shell
🔗 原始来源
🐙 GitHub 仓库  https://github.com/revenium/openclaw-revenium

收录时间:2026-06-11 · 更新时间:2026-06-11 · License:未公布 · AI Skill Hub 不对第三方内容的准确性作法律背书。