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human-handoff-coordinator人类交接协调员

Agent Skill

human-handoff-coordinator 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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

8,760

周安装

365

GitHub Stars

公开资料未说明

下载量

2,920
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:human-handoff-coordinator(人类交接协调员)
来源仓库:https://github.com/danyangliu-sandwichlab/human-handoff-coordinator
安装命令:
openclaw skills install human-handoff-coordinator
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 human-handoff-coordinator

简介

将自动化对话升级为与人类广告专家进行 Meta (Facebook/Instagram)、Google Ads、TikTok 广告和 YouTube 广告运营的自动化对话。

SKILL.md

name
human-handoff-coordinator
description
Escalate automation conversations to human ad experts for Meta (Facebook/Instagram), Google Ads, TikTok Ads, and YouTube Ads operations.

Ads Human Handoff

Purpose

Core mission:

  • handoff packet creation, escalation routing

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

When To Trigger

Use this skill when the user asks for:

  • ad execution guidance tied to business outcomes
  • growth decisions involving revenue, roas, cpa, or budget efficiency
  • platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads
  • this specific capability: handoff packet creation, escalation routing

High-signal keywords:

  • ads, advertising, campaign, growth, revenue, profit
  • roas, cpa, roi, budget, bidding, traffic, conversion, funnel
  • meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

  • question: user issue or decision request
  • context: account, campaign, and objective context
  • urgency_level

Optional:

  • error_message
  • screenshots_or_logs
  • preferred_response_style

Output Contract

  1. Direct Answer
  2. Root Cause Hypothesis
  3. Immediate Actions
  4. Escalation Criteria
  5. Follow-up Questions

Workflow

  1. Classify question type (how-to, diagnosis, policy, strategy).
  2. Provide shortest valid answer first.
  3. Add context-aware action checklist.
  4. Flag escalation if risk or uncertainty is high.
  5. Return follow-up fields only if required.

Decision Rules

  • If answer confidence is low, state uncertainty and propose verification steps.
  • If issue impacts spend safety, prioritize pause or cap recommendations.
  • If user asks unsupported action, hand off with exact context package.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads

Platform behavior guidance:

  • Keep recommendations channel-aware; do not collapse all channels into one generic plan.
  • For Meta and TikTok Ads, prioritize creative testing cadence.
  • For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
  • For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

  • Never fabricate metrics or policy outcomes.
  • Separate observed facts from assumptions.
  • Use measurable language for each proposed action.
  • Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

  • If critical inputs are missing, ask for only the minimum required fields.
  • If platform constraints conflict, show trade-offs and a safe default.
  • If confidence is low, mark it explicitly and provide a validation checklist.
  • If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Quick Triage JSON

{ "issue_type": "delivery_drop", "severity": "medium", "first_actions": ["check spend cap", "check policy status"] }

Handoff Payload

ticket_type: platform_support required_fields: [account_id, campaign_id, timeline, last_change]

Examples

Example 1: Delivery suddenly dropped

Input:

  • Campaign impressions down 60%
  • No recent manual changes

Output focus:

  • probable causes
  • first 3 checks
  • escalation trigger

Example 2: Policy rejection question

Input:

  • Ad rejected with vague reason
  • User wants fastest fix

Output focus:

  • policy interpretation
  • rewrite direction
  • approval retry order

Example 3: Need human support now

Input:

  • Billing or account lock issue
  • Launch deadline is today

Output focus:

  • handoff packet
  • urgency level
  • required owner and ETA

Quality Checklist

  • [ ] Required sections are complete and non-empty
  • [ ] Trigger keywords include at least 3 registry terms
  • [ ] Input and output contracts are operationally testable
  • [ ] Workflow and decision rules are capability-specific
  • [ ] Platform references are explicit and concrete
  • [ ] At least 3 practical examples are included

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

89.61%
按下载量换算2,617

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。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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