MECE Analysis
SkillDev toolsStructure thinking using Mutually Exclusive, Collectively Exhaustive categories. Use when breaking down problems or ensuring complete coverage.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the MECE Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by itseffi/agentic-os in .agents/skills/mece-analysis/SKILL.md and read by ahel’s review.
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.
Signals
- GitHub stars
- 112
- Forks
- 21
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
mece-analysis- Source
- github.com/itseffi/agentic-os