agentleFS
itseffiitseffi/agentic-os/.agents/skills/mece-analysis/SKILL.md

mece-analysis

Skill114 starsChanged 10 months agoMITView on GitHub

Structure thinking using Mutually Exclusive, Collectively Exhaustive categories. Use when breaking down problems or ensuring complete coverage.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When you need to break down a problem, categorize options, or ensure complete coverage.

    line 12
  2. Distinctive:

    Mutually Exclusive: No overlap between categories

    line 18
  3. Distinctive:

    Collectively Exhaustive: All possibilities covered

    line 19
  4. Distinctive:

    If overlap exists, redefine boundaries

    line 28
  5. Distinctive:

    Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

    line 64

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

MECE Analysis

Structure thinking using Mutually Exclusive, Collectively Exhaustive categories.

When to Use

When you need to break down a problem, categorize options, or ensure complete coverage.

The Principle

MECE = Mutually Exclusive, Collectively Exhaustive

  • Mutually Exclusive: No overlap between categories
  • Collectively Exhaustive: All possibilities covered

The Process

1. Analyze Mutual Exclusivity

For each pair of items:

  • Is there any overlap?
  • Could something belong to both?
  • If overlap exists, redefine boundaries

2. Analyze Collective Exhaustiveness

For the whole set:

  • Are there gaps?
  • What scenarios aren't covered?
  • What's missing?

3. Create Logical Tree

Structure as hierarchy:

  • Top level: Broadest categories
  • Sub-levels: More specific breakdowns
  • Each level should be MECE

Example

Bad (not MECE):

  • Marketing channels: Social, Digital, Facebook, Email
  • (Facebook overlaps with Social and Digital)

Good (MECE):

  • Marketing channels: Paid, Owned, Earned
    • Paid: Social ads, Search ads, Display
    • Owned: Email, Website, App
    • Earned: PR, Reviews, Word of mouth

Output

  • MECE categories with clear boundaries
  • Logical tree showing hierarchy
  • Notes on any gaps or overlaps found

When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.