Token导航 LogoToken导航TokenDH.com
效率权限需确认clawhub未标认证来源可访问clear审计通过

service-qa-coach服务质量保证教练

Agent Skill

service-qa-coach 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

2,864

周安装

117

GitHub Stars

公开资料未说明

下载量

917
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:service-qa-coach(服务质量保证教练)
来源仓库:https://github.com/harrylabsj/service-qa-coach
安装命令:
openclaw skills install service-qa-coach
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 service-qa-coach

简介

评估客服团队服务质量并提供改进建议。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

  • 分析聊天记录、邮件与电话交互的质量缺陷模式。
  • 输出 QA 评分卡与辅导要点,支持培训材料生成。
  • 需上传历史工单样本作为分析依据。service-qa-coach 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 建议每月迭代评分维度以适应业务变化。

SKILL.md

name
service-qa-coach
description
Review support quality for chat, email, phone, social DM, or marketplace service teams. Use when a team needs a QA scorecard, failure-mode analysis, coaching plan, calibration checklist, or service-improvement brief without live ticketing, CRM, or contact-center system access.

Service QA Coach

Overview

Use this skill to turn support quality concerns into a structured QA and coaching brief. It helps define the scorecard, isolate likely failure modes, recommend coaching actions, and organize a sampling and calibration rhythm.

This MVP is heuristic. It does not connect to live ticketing systems, call recordings, chat exports, CRMs, or QA platforms. It relies on the user's provided support notes, issue patterns, and service expectations.

Trigger

Use this skill when the user wants to:

  • audit customer service quality across chat, email, phone, social DM, or marketplace tickets
  • build or refine a QA rubric for support teams
  • diagnose recurring service failures such as poor empathy, policy errors, or weak resolution quality
  • create a coaching plan for agents, team leads, or new hires
  • run a calibration sprint before changing SOPs or scorecards

Example prompts

  • "Help me build a QA scorecard for our live chat team"
  • "Why are refund escalations rising in customer service?"
  • "Create a coaching plan for agents with low empathy and policy accuracy"
  • "Turn these support issues into a QA and calibration brief"

Workflow

  1. Capture the support channel, review mode, and quality concern.
  2. Choose the focus areas such as compliance, empathy, resolution, speed, or documentation.
  3. Identify the likely failure modes and coaching priorities.
  4. Define sampling, calibration, and follow-up rhythm.
  5. Return a markdown QA coaching brief.

Inputs

The user can provide any mix of:

  • support channel such as chat, email, phone, social DM, or marketplace tickets
  • quality goals such as CSAT recovery, policy compliance, or escalation reduction
  • issue notes such as slow responses, low empathy, incorrect policy answers, or poor note-taking
  • team context such as new hires, macro usage, QA backlog, or uneven supervisor coaching
  • sample size, review cadence, and escalation process assumptions

Outputs

Return a markdown QA coaching brief with:

  • QA summary
  • scorecard rubric
  • failure mode review
  • coaching plan
  • calibration and sampling guidance
  • assumptions and limits

Safety

  • Do not claim access to live tickets, recordings, or customer records.
  • Do not invent agent-level performance facts that were not supplied.
  • Privacy, compliance, refund, and disciplinary decisions remain human-approved.
  • Reduce certainty when the sample is tiny or anecdotal.

Best-fit Scenarios

  • service teams that need a lighter QA framework before investing in tooling
  • ecommerce operators managing outsourced or mixed support teams
  • managers trying to reduce escalations, refunds, or poor customer sentiment

Not Ideal For

  • live contact-center monitoring or real-time QA enforcement
  • regulated complaint handling that requires legal or compliance review
  • detailed workforce management or call-center forecasting

Acceptance Criteria

  • Return markdown text.
  • Include rubric, coaching, calibration, and limits sections.
  • Keep the no-live-data framing explicit.
  • Make the output practical for team leads and support managers.

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

94.66%
按下载量换算868

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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

继续浏览同类 Skills