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arc-workflow-orchestratorarc 工作流编排器

Agent Skill

arc-workflow-orchestrator 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

总安装

56,384

周安装

2,422

GitHub Stars

1

下载量

19,764
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:arc-workflow-orchestrator(arc 工作流编排器)
来源仓库:https://github.com/trypto1019/arc-workflow-orchestrator
安装命令:
openclaw skills install arc-workflow-orchestrator
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 arc-workflow-orchestrator

简介

将技能链接至自动化管道,支持条件逻辑与错误处理流程。

  • 通过 YAML/JSON 定义工作流并手动或定时执行。
  • 通过 OpenClaw 的 clawhub 安装,需集成编排引擎与状态机。
  • 建议设置回滚机制,避免单次失败影响整体流程。arc-workflow-orchestrator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 适合复杂业务场景下的多技能协同与流程标准化。

SKILL.md

name
workflow-orchestrator
description
Chain skills into automated pipelines with conditional logic, error handling, and audit logging. Define workflows in YAML or JSON, then execute them hands-free. Perfect for security-gated deployments, scheduled maintenance, and multi-step agent operations.
user-invocable
true
metadata
{"openclaw": {"emoji": "🔗", "os": ["darwin", "linux"], "requires": {"bins": ["python3"]}}}

Workflow Orchestrator

Chain skills into automated pipelines. Define a sequence of steps, and the orchestrator runs them in order with conditional logic, error handling, and optional audit logging.

Why This Exists

Agents run multiple skills but manually. Scan a skill, diff against the previous version, deploy if safe, log the result. That's 4 steps, 4 commands, and one missed step means a gap in your process. Workflows automate the sequence and ensure nothing gets skipped.

Commands

Run a workflow from a YAML file

python3 {baseDir}/scripts/orchestrator.py run --workflow workflow.yaml

Run a workflow from JSON

python3 {baseDir}/scripts/orchestrator.py run --workflow workflow.json

Dry run (show steps without executing)

python3 {baseDir}/scripts/orchestrator.py run --workflow workflow.yaml --dry-run

List available workflow templates

python3 {baseDir}/scripts/orchestrator.py templates

Validate a workflow file

python3 {baseDir}/scripts/orchestrator.py validate --workflow workflow.yaml

Workflow Format (YAML)

name: secure-deploy
description: Scan, diff, deploy, and audit a skill update
steps:
  - name: scan
    command: python3 ~/.openclaw/skills/skill-scanner/scripts/scanner.py scan --path {skill_path} --json
    on_fail: abort
    save_output: scan_result

  - name: diff
    command: python3 ~/.openclaw/skills/skill-differ/scripts/differ.py diff {skill_path} {previous_path}
    on_fail: warn

  - name: deploy
    command: python3 ~/.openclaw/skills/skill-gitops/scripts/gitops.py deploy {skill_path}
    condition: scan_result.verdict != "CRITICAL"
    on_fail: rollback

  - name: audit
    command: python3 ~/.openclaw/skills/compliance-audit/scripts/audit.py log --action "skill_deployed" --details '{"skill": "{skill_name}", "scan": "{scan_result.verdict}"}'
    on_fail: warn

Step Options

  • name — Human-readable step name
  • command — Shell command to execute (supports variable substitution)
  • on_fail — What to do if the step fails: abort (stop workflow), warn (log and continue), rollback (undo previous steps), retry (retry up to 3 times)
  • condition — Optional condition to check before running (references saved outputs)
  • save_output — Save stdout to a named variable for use in later steps
  • timeout — Max seconds to wait (default: 60)

Variable Substitution

Use {variable_name} in commands to reference:

  • Workflow-level variables defined in the vars section
  • Saved outputs from previous steps
  • Environment variables with {env.VAR_NAME}

Built-in Templates

The orchestrator ships with these workflow templates:

  1. secure-deploy — Scan → Diff → Deploy → Audit
  2. daily-scan — Scan all installed skills, report findings
  3. pre-install — Scan → Typosquat check → Install → Audit

Example: Secure Deploy Pipeline

name: secure-deploy
vars:
  skill_path: ~/.openclaw/skills/my-skill
  skill_name: my-skill
steps:
  - name: security-scan
    command: python3 ~/.openclaw/skills/skill-scanner/scripts/scanner.py scan --path {skill_path} --json
    save_output: scan
    on_fail: abort
  - name: deploy
    command: echo "Deploying {skill_name}..."
    condition: "CRITICAL not in scan"
    on_fail: abort
  - name: log
    command: python3 ~/.openclaw/skills/compliance-audit/scripts/audit.py log --action workflow_complete --details '{"workflow": "secure-deploy", "skill": "{skill_name}"}'

Tips

  • Start with --dry-run to verify your workflow before executing
  • Use on_fail: abort for security-critical steps
  • Chain with the compliance audit skill for full traceability
  • Keep workflows in version control for reproducibility

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.87%
按下载量换算15,786

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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