‹ 首页

client-health-dashboard

@pmkshar · 收录于 1 周前 · 上游提交 1 周前

Generates a comprehensive client health overview across all accounts. Reads CRM data, support tickets, usage metrics, billing, and engagement logs. Calculates health scores, trend direction, and RAG status per client. Outputs a sorted risk report with recommended actions.

适合你,如果需要跨账户监控客户状态并识别风险客户。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add pmkshar/marqaiskills/client-health-dashboard
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- pmkshar/marqaiskills/client-health-dashboard
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify pmkshar/marqaiskills/client-health-dashboard
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
0GitHub stars
~692最小装载
~3.7K含声明引用
~3.7K文本包总量
索引托管

怎么用

商店整理自技能原文 · 版本 d5999f8 · 表述以原文为准
它做什么

装上后,Claude 会从 CRM、工单、使用数据、账单和沟通记录中收集信息,为每个客户计算健康分数,并生成一份按风险排序的报告,包含红黄绿状态和具体建议。

什么时候触发

当你要求生成客户健康报告时触发,例如说“生成客户健康概览”或“检查客户风险”。

装好后可以这样说
报告将仅包含这两个客户。
Claude 会优先解析你提供的文件作为数据源。
技能原文 SKILL.md作者撰写 · MIT · d5999f8

Client Health Dashboard

Generate a data-driven client health report: pull data from every available source, compute a weighted health score per client, and produce a prioritized risk report (client-health-report.md) sorted by risk with RAG status and actionable recommendations.

Contents
  • references/data-sources.md -- what to pull from CRM, support, usage, billing, and communication channels
  • references/scoring-model.md -- dimensions, weights, scoring rules, composite formula, RAG thresholds, trend logic
  • references/risk-and-recommendations.md -- risk factor triggers, per-dimension recommendation menus, expansion assessment
  • references/output-format.md -- exact report structure, formatting rules, and missing-data handling
Workflow
  1. Collect data from every available source. Handle failures gracefully: log what was unavailable and proceed with partial data. Never fabricate data. See references/data-sources.md for the full source list and the fields to extract per client.
  2. Score each client. Rate the five dimensions 0-100, apply weights, and compute the composite score. Assign RAG status and trend direction. See references/scoring-model.md.
  3. Analyze risk and generate recommendations. Flag critical and warning risk factors, produce 2-4 specific recommendations targeting each client's weakest dimensions, and assess expansion potential for healthy accounts. See references/risk-and-recommendations.md.
  4. Generate the report. Write client-health-report.md following the exact structure and formatting rules. Handle missing data by scoring neutral (50) and noting gaps. See references/output-format.md.
  5. Validate before finalizing:
  6. Verify RAG assignments match score ranges.
  7. Confirm section ordering and within-section sorting.
  8. Confirm every client appears exactly once.
  9. Confirm each client has 2-4 specific, actionable recommendations.
  10. Attribute each data point to its source.
  11. Mark data gaps explicitly; never invent data that was not retrieved.
Interaction
  • If the user specifies particular clients, filter the report to those only.
  • If the user specifies a data source, prioritize it.
  • If the user provides CSV/Excel files, parse them as a primary source.
  • If the user requests a format variation, adapt accordingly.
  • Confirm the output path before writing.
  • If no data sources are accessible, explain what is needed and what to provide.
Constraints
  • Never fabricate or hallucinate data; report only what was retrieved, attributed to its source.
  • Never include credentials, API keys, or PII beyond business contact info.
  • Keep health scores mathematically correct per the weighting formula.
  • Keep recommendations specific and actionable, not generic.
  • Keep the report self-contained, professional, and direct.
  • Do not use emojis anywhere in the report or any output.
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

登录即可评论;带「已验证安装」的,是发布者名下有本店的安装或持有记录。