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consulting-issue-tree-mece咨询问题树 mece

Agent Skill

用于围绕 GitHub 仓库、Issue、Pull Request、分支、提交和代码协作流程提供辅助能力。它适合让 Agent 查询项目状态、整理变更、辅助创建或检查协作事项,并把仓库中的信息转成可执行的下一步。使用时需要区分只读查询和写入操作;涉及创建 PR、修改 Issue、推送分支或访问私有仓库时,应确认 token 权限、目标仓库范围和用户授权。

总安装

1,173

周安装

47

GitHub Stars

1

下载量

380
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

3

许可证

MIT

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:consulting-issue-tree-mece(咨询问题树 mece)
来源仓库:https://github.com/santos-sanz/lifeskills
仓库路径:skills/consulting-issue-tree-mece
安装命令:
npx skills add https://github.com/santos-sanz/lifeskills --skill consulting-issue-tree-mece
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/santos-sanz/lifeskills --skill consulting-issue-tree-mece

简介

使用 MECE 原则构建互斥且穷尽的问题树,定位根本原因。

  • 支持驱动因素、流程和选项等多种树形结构建模。
  • 适用于性能下降诊断和战略问题的结构化分析。
  • 需明确问题陈述、基线指标和时间边界等输入要素。
  • consulting-issue-tree-mece 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

MECE Issue Tree

Use $ARGUMENTS as initial context.

When to use this skill

  • Diagnosing root causes in performance decline or execution failures.
  • Structuring strategic questions into mutually exclusive branches.
  • Creating a prioritized analysis plan before data deep-dives.
  • Aligning teams on problem scope and ownership.

Required inputs

  • Problem statement, metric, and baseline.
  • Scope boundaries (segment, geography, time horizon).
  • Available data and decision deadline.

Workflow

  1. Convert the request into one decision-oriented problem statement.
  2. Select tree type: driver, process, option, or hypothesis tree.
  3. Build 2-3 levels of MECE branches with parallel labels.
  4. Run formal checks for overlap, gaps, and level-mixing.
  5. Prioritize branches by impact, controllability, and learning speed.
  6. Translate top branches into an analysis backlog with owners and timing.

Ask-first questions

Ask up to 3 questions before building the tree:

  1. Which metric and baseline define the problem severity?
  2. What scope is explicitly in or out?
  3. What decision must this tree support?

Assumption policy

  • Proceed if data is incomplete, but list assumptions in a dedicated section.
  • Tag assumptions with confidence and validation path.
  • Do not invent branch evidence; flag unknowns explicitly.

Output contract

Always produce these sections in order:

  1. Context
  2. Decision or Recommendation
  3. Analysis
  4. Risks
  5. Next Actions
  6. Assumptions

Guardrails

  • No branch overlap at the same level.
  • No mixing causes and outcomes in one branch layer.
  • No "other" bucket unless unavoidable and quantified.
  • Keep branch naming at equivalent abstraction depth.

Resources

  • references/issue-tree-patterns.md - Tree patterns and branch design rules.
  • references/mece-checks.md - Validation gates and failure diagnostics.
  • templates/issue-tree.md - Decision-ready tree template.
  • examples/issue-tree-example.md - Golden example with partial information.

Keywords

issue tree, MECE, root cause, problem structuring, analysis backlog, driver tree

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

04

需要参考平台分布和安装热度时

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

OpenCode

28.42%
按下载量换算108

windsurf

23.01%
按下载量换算87

trae

17.66%
按下载量换算67

Cursor

13.08%
按下载量换算50

kiro-cli

8.42%
按下载量换算32

Codex

3.59%
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。

来源信息

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