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cs-sopCS SOP 命令行

Agent Skill

cs-sop 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

461

周安装

19

GitHub Stars

124

下载量

150
CodexClaudeCursorGemini CLI

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

unknown

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:cs-sop(CS SOP 命令行)
来源仓库:https://github.com/asgard-ai-platform/skills
仓库路径:skills/cs-sop
安装命令:
npx skills add https://github.com/asgard-ai-platform/skills --skill cs-sop
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/asgard-ai-platform/skills --skill cs-sop

简介

cs-sop 提供客户服务标准作业程序,采用三级支持模型按问题复杂度分流。

  • L1 处理 FAQ、密码重置等简单事务,目标 <5 分钟首次解决;L2 处理技术问题;L3 需工程介入。
  • IRON LAW:按 ISSUE COMPLEXITY 分流,非按客户重要性分配资源。
  • 适用于规模化 CS 组织建设,包含团队结构、分段策略与技术栈选型。
  • 需配合 metrics 关注 outcomes 而非 activities,CS 拥有 NDR 等关键指标。

SKILL.md

Customer Service SOP

Framework

IRON LAW: Tier the Support, Not the Customer

Every customer deserves quality service. But not every issue needs a
senior specialist. Route by ISSUE COMPLEXITY, not by customer "importance."

L1 handles 70-80% of volume (simple, repeatable)
L2 handles 15-20% (requires expertise)
L3 handles 5% (requires engineering or management)

Three-Tier Support Model

TierHandlesSkills RequiredResolution Target
L1 (Basic)FAQ, order status, password reset, simple returnsScript-following, product basics, empathy< 5 minutes, first-contact resolution
L2 (Specialist)Technical issues, billing disputes, complex returns, product defectsDeep product knowledge, judgment, negotiation< 24 hours
L3 (Expert)System bugs, legal/compliance, executive escalations, crisisEngineering, legal, or management involvement< 72 hours, case-by-case

Case Categorization

CategoryExamplesPrioritySLA (First Response)
CriticalService outage, security breach, safety issueP1< 15 minutes
HighPayment failure, account locked, order errorP2< 1 hour
MediumProduct question, feature request, general complaintP3< 4 hours
LowFeedback, suggestion, general inquiryP4< 24 hours

Complaint Handling: LAST Framework

  1. Listen: Let the customer express fully without interrupting
  2. Apologize: Acknowledge their frustration sincerely ("I'm sorry this happened")
  3. Solve: Offer a concrete solution or next step
  4. Thank: Thank them for bringing it to your attention

Escalation Rules

TriggerEscalate ToTimeline
L1 can't resolve in 15 minL2Immediate warm handoff
Customer requests supervisorL2 or Team LeadWithin 5 minutes
Issue involves refund > NT$XL2 (approval authority)Same interaction
Legal threat or media mentionL3 + Legal + PRImmediate
Repeat contact (3+ on same issue)L2 + investigationAfter 3rd contact

Response Template Structure

[Greeting] Hi {name}, thank you for contacting us.

[Acknowledge] I understand you're experiencing {issue}.

[Action] Here's what I've done / Here's what we'll do:
1. {specific action}
2. {timeline}

[Next steps] {what the customer should expect / do next}

[Close] Is there anything else I can help you with?

Output Format

# Customer Service SOP: {Business}

## Support Tiers
| Tier | Scope | Team Size | Tools |
|------|-------|----------|-------|
| L1 | {scope} | {N people} | {tools} |
| L2 | {scope} | {N} | {tools} |
| L3 | {scope} | {N} | {tools} |

## SLA Targets
| Priority | First Response | Resolution | Escalation |
|----------|--------------|-----------|-----------|
| P1 | {time} | {time} | {to whom} |
| P2 | ... | ... | ... |

## Top 10 Contact Reasons
| # | Reason | Volume % | Resolution | Template? |
|---|--------|---------|-----------|----------|
| 1 | {reason} | {%} | L1/L2 | Y/N |

## Escalation Flowchart
{Decision tree for when to escalate}

## Quality Metrics
| Metric | Target |
|--------|--------|
| First Contact Resolution | > 70% |
| CSAT | > 4.2/5 |
| Avg Response Time | < {X} hours |
| Escalation Rate | < 20% |

Gotchas

  • SLAs must be MEASURABLE: "Respond quickly" is not an SLA. "First response within 1 hour for P2 tickets" is. If you can't measure it, you can't manage it.
  • Warm handoff > cold transfer: When escalating, the L1 agent should brief L2 before transferring. Forcing the customer to repeat their story destroys satisfaction.
  • Empower L1 with resolution authority: If L1 must escalate every refund, 70% of volume goes to L2 unnecessarily. Give L1 authority for refunds under a threshold (e.g., NT$500).
  • Templates are starting points, not scripts: Robotic copy-paste responses feel worse than no response. Agents should personalize templates to the specific situation.
  • Taiwan CS expectations: Taiwan customers expect fast LINE response (within minutes during business hours), polite and apologetic tone, and willingness to go the extra mile. The bar for "good service" is high.

References

  • For CSAT/NPS survey design, see the cs-analytics skill
  • For chatbot-human handoff design, see the cs-chatbot-design skill

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

36.18%
按下载量换算54

Claude

28.42%
按下载量换算43

Cursor

19.1%
按下载量换算29

Gemini CLI

9.13%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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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