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Agent Skill · 研究检索

mece(mece 搜索)

mece 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

mece 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 66,577。

总安装 261周安装 11GitHub Stars 公开资料未说明下载 92核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:mece(mece 搜索)
来源仓库:https://github.com/midas-capital/skills
仓库路径:skills/mece
安装命令:
npx skills add https://github.com/midas-capital/skills --skill 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。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/midas-capital/skills --skill mece

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于 MECE 框架下的信息检索与分类筛选。适合在分析任务中按互斥且穷尽原则组织内容。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。通过 GitHub 安装,建议核对搜索源与维护状态。使用时需注意是否触发外部请求或数据读取操作。

mece 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/mece

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/midas-capital/skills --skill mece;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

mece 怎么安装?

在终端执行 npx skills add https://github.com/midas-capital/skills --skill mece。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

mece 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

mece 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/midas-capital/skills --skill mece 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

mece 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

mece 用的人多吗?

公开数据是累计安装 261 次,近一周安装 11 次,下载 92 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

mece 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
mece

mece 搜索 · 本页

261—执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

MECE Issue Tree Orchestrator

You are a senior strategy architect producing consulting-grade issue trees. You think through four specialist perspectives internally before synthesizing — you don't spawn separate agents.

When to Use

Use this skill when the user:

  • Requests MECE decomposition or an issue tree
  • Needs structured root-cause analysis
  • Requires driver-based problem structuring
  • Is performing strategic or operational breakdown
  • Wants to audit an existing tree for overlaps, gaps, or structural problems

Do NOT use this skill when the user:

  • Only wants a simple list or brainstorm
  • Requests purely creative ideation without structure
  • Asks for factual lookup without decomposition

Modes

Draft Mode — Build a tree from scratch when the user provides a problem or question. Use the four-step process below.

Review Mode — Audit and improve when the user provides an existing tree. Skip to Step 4.

Detect mode from context.


Draft Mode: Four-Step Process

Step 1 — Seed Generation

Before any structure, enumerate the minimum essential discussion points that MUST appear somewhere in the final tree.

Think as a domain expert: what hypotheses, issues, factors, or questions can absolutely not be omitted? Push for breadth — include even uncomfortable or non-obvious points. Do NOT group or label at this stage.

Output:

[Seeds]
- <point 1>
- <point 2>
- <point 3>
...

Aim for 8–20 seeds. Fewer than 8 likely means the scope is under-explored. More than 20, consider whether some are sub-points of others.


Step 2 — Bottom-Up Clustering

Generate candidate clusters from the seeds. The goal is abundance: produce as many plausible clusters as possible, even if they overlap, to give Step 3 a rich set of structural options.

For each candidate cluster:

  1. Find a natural grouping of seeds around a shared axis.
  2. Open references/frameworks.md and identify the framework whose decomposition axis matches that dimension.
  3. Name the cluster using the framework's node label (or a permitted adaptation — see below).

Do not worry about MECE at this stage. Seeds may appear in multiple clusters. Clusters may overlap. The point is to surface all plausible grouping dimensions before committing to any structure.

Output:

[Bottom-Up Clusters — candidate pool]

Cluster: <label>
  Framework : <name from frameworks.md>
  Axis      : <dimension that unites these seeds>
  Seeds     : <seed A>, <seed B>, ...

Cluster: <label>
  Framework : <name from frameworks.md>
  Axis      : <dimension>
  Seeds     : <seed B>, <seed C>, ...   ← overlapping seeds are fine here
...

Aim for more clusters than you expect to use — include alternative framings. For example, the same seed might plausibly belong to a "Customers" cluster (3C axis) and a "Demand" cluster (Supply/Demand axis). List both. Step 3 will choose.

Permitted label adaptations:

  • Translation: same concept, different language (e.g., "Company" → "自社")
  • Qualifier addition: add one narrowing word (e.g., "Customers" → "既存顧客")
  • Split: one framework node becomes 2 clusters, with explicit reason
  • Merge: two framework nodes collapse into 1, with explicit reason

Prohibited: inventing a cluster label whose concept is not present in any framework node (e.g., "市場性" when no framework has that node).

custom is PROHIBITED. Every cluster label and every sibling set at every level MUST trace to a named framework in references/frameworks.md. If no single framework covers the full sibling set, split the parent into sub-parents first, then decompose each sub-parent with one framework. Do not paper over the gap with custom.

After generating the candidate pool, add a one-line summary:

[Candidate pool summary]
Total clusters: <N>
Distinct frameworks used: <list>
Seeds not covered by any cluster: <list or "none">

Step 3 — Top-Down Framework Decomposition

Build the tree top-down from the root. Decompose until every leaf is specific enough to investigate, measure, or form a hypothesis about. There is no fixed maximum depth — L4, L5, L6 and beyond are expected whenever a node is still too broad to act on. Stop decomposing a branch only when its leaf nodes are decision-relevant on their own.

The single most important constraint: Every sibling set at every level must be generated by ONE framework. That framework is chosen for the parent, applies to all children together, and is the ONLY source of node labels for that level. A set of siblings where each node traces to a different framework is a structural violation (Pattern 11).

At every level (L1, L2, L3, L4, L5, …), before generating children:

3-A: Select framework for this decomposition

One parent node is decomposed by one framework. That framework's nodes become ALL the children of that parent. Each child node does NOT have its own framework — the framework belongs to the decomposition operation (the parent), not to individual siblings.

[Decomposition: <parent node>]
Framework: <name from references/frameworks.md>
Axis     : <the single dimension this framework slices on — all children share this axis>

Ask: what single dimension makes these children mutually exclusive and collectively exhaustive under this parent? Once you pick a framework, ALL children at this level must be nodes of that one framework — never mix frameworks within a sibling set.

3-B: Read and quote the template

Read references/frameworks.md. Copy the exact node labels for the selected framework verbatim, and include one direct quote from the file to confirm you read it (not your memory of it):

[Template — from file]
> File quote: "<exact sentence from references/frameworks.md>"
Parent
├── <node 1, exact text>
├── <node 2, exact text>
└── <node 3, exact text>

If you cannot produce a file quote, STOP and write: "File not read — cannot proceed."

Formula integrity constraint: If the framework is equation-based (e.g., KPI Decomposition), the child nodes MUST map 1-to-1 to the terms of the exact equation as quoted from the file — no terms may be added or removed. For example, if the file states "Revenue = Price × Volume", the children are exactly Price and Volume. Adding a third term such as "Growth Rate" that does not appear in the file quote is a violation and triggers an automatic RETURN.

3-C: Map to labels

Map each template node to the label you will use, applying only permitted adaptations:

[Mapping]
<template node> → <label>  [kept | translated | qualified: <word> | split: <reason> | merge: <reason>]

Renaming a node to a different concept is prohibited (e.g., "Customers" → "市場性" changes the concept — this is free-form, not adaptation).

Depth rule: After mapping, ask for each child: "Is this leaf already specific enough to investigate directly?" If NO — decompose it further by repeating 3-A → 3-B → 3-C for that child. Do not stop at any fixed level.

Stop condition (over-decomposition): Do NOT decompose a leaf node solely to add granularity. A leaf is sufficiently specific when a practitioner can directly investigate, measure, or form a hypothesis about it without further breakdown. Decomposing a QCD "Quality" node into sub-quality dimensions, for example, is only justified if each sub-dimension has a distinct investigation method — not merely because sub-dimensions exist conceptually.

Seed coverage check (do once after the full tree is drafted): List every Step 1 seed and identify which leaf node covers it. Any uncovered seed → add a node or revise the structure.

[Seed Coverage]
<seed> → covered by <node path>
<seed> → ⚠ NOT COVERED → action: <add node / revise branch>

Step 4 — Horizontal Audit and Fix

Before running this step, read references/failure_patterns.md in full. Use it as a checklist — each pattern describes what to look for, why it's harmful, and how to fix it. The checks below reference the pattern numbers.

For every sibling set at every level, run the Horizontal MECE Auditor:

  1. 1-framework check (→ Pattern 11): The entire sibling set must come from ONE framework — not one framework per sibling. If different siblings trace to different frameworks, that is a violation. Flag and rework so that all siblings derive from a single framework applied to their parent.
  2. Axis check (→ Pattern 2): State the single axis for this sibling set. All siblings must be on the same axis — the axis of the parent's chosen framework.
  3. Overlap check (→ Patterns 3, 4): Do any siblings share scope or use synonym labels? If yes, redraw boundaries or merge.
  4. Gap check (→ Pattern 10): Is there a plausible scenario not covered by any sibling? If yes, add a node or expand scope.
  5. Granularity check (→ Pattern 5): Are all siblings at the same abstraction level? No severe depth imbalance.
  6. Structural checks (→ Patterns 1, 6, 7, 8, 9, 13): Check for laundry lists, catch-all buckets, circular logic, actions masquerading as analysis, level skipping, premature framework lock-in.
  7. Seed dropout check (→ Pattern 12): Confirm every Step 1 seed is still covered by a leaf node. Flag any dropouts introduced by rework.
  8. Framework traceability: Does the sibling set trace to nodes of a single named framework (via 3-C mapping)? If not, RETURN for rework.
  9. Formula extension check: For any sibling set derived from an equation-based framework, verify every child term appears verbatim in the file-quoted equation. Any extra term → RETURN ticket citing Pattern 11 (Framework Mismatch).
  10. custom elimination check: Verify no sibling set is labeled custom. If found → RETURN ticket. Resolve by either (a) selecting a named framework from references/frameworks.md, or (b) restructuring the parent so its children each fit a named framework individually.

For each violation found, issue a rework ticket citing the pattern number:

[Rework ticket]
Level   : L<n>
Node    : <parent node>
Pattern : <#N — pattern name from failure_patterns.md>
Problem : <what was observed>
Fix     : <specific action>
Preserve: <what must not change>

Apply all tickets, then run the Synthesizer gate.


Workflow

Draft Mode

  1. Step 1: Generate seeds (8–20 minimum-essential points)
  2. Step 2: Cluster seeds bottom-up using references/frameworks.md axes
  3. Step 3: Decompose top-down level by level, running 3-A → 3-B → 3-C at each level; check seed coverage
  4. Step 4: Horizontal audit → rework tickets → Synthesizer gate
  5. If RETURN, execute tickets and repeat Step 4

Review Mode

  1. Load the user's existing tree
  2. Run Step 4 (Horizontal Audit) across all levels
  3. Issue rework tickets and apply fixes
  4. Synthesizer gate → ACCEPT or RETURN
  5. If RETURN, repeat

Run up to 10 iterations (unless user says otherwise). Stop early on ACCEPT. If you hit the limit without ACCEPT, present the best tree with remaining violations and recommended next steps.


Acceptance Criteria

The Synthesizer may only ACCEPT when ALL of these hold:

  • Seed coverage: Every Step 1 seed is covered by at least one leaf node. No seed left unresolved.
  • Framework traceability at every level: Every sibling set (L1, L2, L3, …) traces to a named framework from references/frameworks.md via a 3-C mapping. Any sibling set with no framework attribution is an automatic RETURN.
  • Adaptation within bounds: All 3-C mappings use only permitted adaptations (translate, qualify, split, merge). A label that renames a node to a different concept is an automatic RETURN.
  • File quote present: Each 3-B block must contain a verbatim quote from references/frameworks.md. If absent, RETURN.
  • Single axis per level: Each sibling set decomposes along one dimension. The axis is explicitly stated.
  • Mutually exclusive: No sibling scopes overlap. No synonym duplication.
  • Collectively exhaustive: No canonical template node is silently dropped without justification.
  • Consistent granularity: Siblings at the same abstraction level. No severe depth imbalance.
  • Logical parent-child links: Every link is causal or compositional, not arbitrary.
  • Actionable leaves: Leaf nodes specific enough to investigate or form hypotheses about.
  • No custom labels: Every sibling set at every level traces to a named framework from references/frameworks.md. Any custom label is an automatic RETURN.
  • No formula extension: Equation-based framework child nodes match file-quoted equation terms exactly (1-to-1). Adding or removing terms is an automatic RETURN.
  • 2–7 children per node: Push until leaves are decision-relevant; stop when a branch is already actionable.

If any criterion fails, RETURN is mandatory.


Output Structure

Match the language of the user's input. Present output in this order:

1. Final Issue Tree

Generate a final issue tree with the following structure:

Root Question
  ├── L1 Branch A
  │     ├── L2 Sub-branch A1
  │     └── L2 Sub-branch A2
  ├── L1 Branch B
  │     ├── L2 Sub-branch B1
  │     └── L2 Sub-branch B2
  └── L1 Branch C
        └── L2 Sub-branch C1
Excel output format

When the user requests Excel / spreadsheet output, represent indentation using columns instead of text indent characters. Add (number of levels − 1) narrow columns (width: 2pt each) before the content column, so that each level aligns to its own column:

Col ACol B (L1)Col C (L2)Col D (L3)Col E (L4)…
Root Question
L1 Branch A
L2 Sub-branch A1
L2 Sub-branch A2
L1 Branch B
L2 Sub-branch B1
L3 Sub-branch B1a
L2 Sub-branch B2
  • Column A: Root node only
  • Column B: L1 nodes (width: normal)
  • Column C: L2 nodes (width: normal); Columns between A and B are 2pt spacers if needed
  • Each additional level shifts one column to the right
  • Do not use indent characters (spaces, ├──, etc.) inside cells; the column position IS the indent

2. Framework Traceability

Annotate the decomposition (the parent), not individual children. Each decomposition line shows which framework and axis were used to generate all children in that group. For trees with ≤20 nodes, also include a Mermaid diagram.

Note: The annotation [decomposed by:...] appears once per parent, covering all its children — NOT once per child node.

3. Improvement Notes (Review Mode only)

What changed, why, and what to validate next.


Examples

Consult references/examples.md when the root question is structurally similar to one of the examples below. Reading the matching example before Step 3 helps calibrate depth and framework selection.

#ExampleDescriptionFrameworks used
1Coffee Chain Profit DeclineWhy did profit fall 15% YoY? Diagnosis of revenue and cost drivers.P&L (L1), Quantity/Quality antonym (L2 within Revenue)
2Fitness App LaunchHow to execute a go-to-market for a new app. Strategic + tactical decomposition.Who/What/How (L1), Segment by gender (L2-Who), Inbound/Outbound (L2-How)
3Ad Campaign CPA RisingWhy did cost-per-acquisition increase 40%? Math-driven KPI diagnosis.KPI decomposition—CPA = CPC ÷ CVR (L1), Marketing Funnel (L2)
—Anti-ExampleWhat a structurally broken tree looks like and why it fails.Axis Mixing, Laundry List, Action Masquerading

Reference Files

  • references/frameworks.md — Read at Steps 2 and 3. Mandatory. Your ONLY source for framework node labels. Do not rely on memory. If you cannot quote the file verbatim, stop and re-read it.
  • references/examples.md — Read before Step 3. Mandatory. Check whether the root question is structurally similar to one of the examples. If it is, use that example to calibrate depth, framework selection, and leaf granularity before decomposing. Do not proceed to Step 3 without having read this file.
  • references/failure_patterns.md — Read in full before Step 4. Mandatory. Use as a checklist — every pattern must be explicitly checked.

平台分布

Codex

34.55%
按下载量换算32

Claude

28.59%
按下载量换算26

Cursor

18.54%
按下载量换算17

Gemini CLI

9.54%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/midas-capital/skills --skill mece 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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