搜索

PythonReactSEOPDF
GitHub Skill

map-audit

For leaders evaluating dashboards, metrics, or AI-generated reports to determine if they measure reality or generate confident-looking noise (Potemkin maps). Helps identify gaming potential, blind spots, and whether you should trust a metric more, less, or differently. Use when implementing new metrics, questioning existing dashboards, evaluating vendor claims, or when something feels off about your data. Keywords: dashboard audit, metrics, KPIs, gaming, Goodhart's law, AI reports, data quality, measurement validity, blind spots, Potemkin, are my metrics real, can I trust this data

az9713☆ 0 仓库 Stars0 仓库 Forks

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

查看来源 ↗使用指南

技能说明

功能与用途

For leaders evaluating dashboards, metrics, or AI-generated reports to determine if they measure reality or generate confident-looking noise (Potemkin maps). Helps identify gaming potential, blind spots, and whether you should trust a metric more, less, or differently. Use when implementing new metrics, questioning existing dashboards, evaluating vendor claims, or when something feels off about your data. Keywords: dashboard audit, metrics, KPIs, gaming, Goodhart's law, AI reports, data quality, measurement validity, blind spots, Potemkin, are my metrics real, can I trust this data

快速开始

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

使用指南 ↗

使用示例

查看来源仓库中的使用示例与配置说明。

查看来源 ↗

来源历史

收录时间
2026-01-20
索引更新时间
2026-01-26
Branch
main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

GitHub ↗

chat Comments (0)

chat_bubble_outline

No comments yet. Be the first to share your thoughts!