mcpbeat

Meta Structured Problem

asgard-ai-platform/meta-structured-problem

Apply structured problem-solving using MECE principle, issue trees, hypothesis-driven approach, and the Pyramid Principle. Use this skill when the user faces a complex, ambiguous problem and needs to decompose it systematically, structure a consulting-style analysis, or organize recommendations clearly — even if they say 'where do I start', 'this problem is too big', 'help me break this down', or 'structure my thinking'.

8k tokens
context cost
the whole folder, loaded on every use
4
files
instructions only
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/asgard-ai-platform/skills --skill meta-structured-problem

What comes with it

27 540 bytes besides the instruction
examples/sample_scenario.md
references/issue-tree-templates.md
references/pyramid-principle.md

The instruction itself

10 sections, as written by the author

Structured Problem Solving

Framework

IRON LAW: MECE or It's Not Structured

Every decomposition must be MECE:
- Mutually Exclusive: No overlap between categories
- Collectively Exhaustive: No gaps — all possibilities covered

"Revenue = New customers + Existing customers" is MECE ✓
"Revenue = Online + Enterprise + Growth" is NOT MECE ✗ (overlapping)

Core Tools

Issue Tree: Decompose a question into sub-questions, MECE at each level

"Why is profit declining?"
├── Revenue declining?
│   ├── Volume down?
│   │   ├── New customer acquisition down?
│   │   └── Existing customer churn up?
│   └── Price down?
│       ├── Discounting increased?
│       └── Mix shift to lower-priced products?
└── Costs increasing?
    ├── COGS up?
    └── OpEx up?

Hypothesis-Driven Approach: Instead of exploring everything, state a hypothesis and test it

  • Form an initial hypothesis ("Profit declined because churn increased")
  • Identify what evidence would prove/disprove it
  • Gather that specific evidence
  • Refine or reject the hypothesis
  • Repeat

Pyramid Principle (Barbara Minto): Structure communication top-down

  • Lead with the answer: Start with the recommendation, not the analysis
  • Group supporting arguments: 3-5 supporting points, MECE
  • Order logically: By argument strength, chronologically, or structurally
  • Detail only when asked: Each level provides more detail for those who want it

80/20 Rule: Focus on the 20% of analysis that drives 80% of the answer. Don't over-analyze secondary branches of the issue tree.

Problem Solving Process

  • Define the problem: "The client's profit has declined 15% YoY. Why, and what should they do?"
  • Structure with an issue tree: MECE decomposition of possible causes
  • Prioritize branches: Which branches are most likely to contain the answer? (80/20)
  • Form hypotheses: "I believe the primary cause is..."
  • Gather evidence: Test each hypothesis with data
  • Synthesize findings: What does the evidence say?
  • Recommend: Present using the Pyramid Principle (answer first)

Output Format

# Structured Analysis: {Problem}

## Problem Statement
{One sentence, specific and measurable}

## Issue Tree
{MECE decomposition — text or visual}

## Hypothesis
{Initial hypothesis with rationale}

## Evidence
| Branch | Hypothesis | Evidence | Verdict |
|--------|-----------|---------|---------|
| {branch} | {sub-hypothesis} | {data found} | Confirmed/Rejected |

## Synthesis (Pyramid Structure)
**Recommendation**: {answer first}

**Supporting Arguments**:
1. {argument 1 with evidence}
2. {argument 2 with evidence}
3. {argument 3 with evidence}

## Next Steps
1. {action item}

Examples

Correct Application

Scenario: "Why is our food delivery app losing market share?"

Issue tree (MECE):

Market share declining
├── Our growth slowing?
│   ├── New user acquisition down?
│   │   ├── Marketing spend reduced?
│   │   └── Conversion rate dropped?
│   └── Existing user activity down?
│       ├── Order frequency declining?
│       └── Users churning?
└── Competitors growing faster?
    ├── New entrant capturing share?
    └── Existing competitor accelerating?

Hypothesis: "Existing user activity is down because order frequency declined after the delivery fee increase."

Evidence: Order frequency dropped 22% in the month after fee increase. ✓

Pyramid: "Reverse the delivery fee increase for high-frequency users. Order frequency dropped 22% post-increase, and 60% of lost orders came from users who ordered 3+/week. A loyalty tier with waived fees for frequent users would recover an estimated 15% of lost share at a cost of NT$X/month."

Incorrect Application

  • Issue tree: "Revenue problem: Online, Marketing, Customer Service" → Not MECE (overlapping categories, not exhaustive). Violates Iron Law.

Gotchas

  • MECE is hard in practice: Perfect MECE is aspirational. Get as close as possible and note where categories blur. "Good enough MECE" beats "perfect but took 3 days."
  • Hypothesis-driven ≠ confirmation bias: The hypothesis is a starting point to guide investigation, not a conclusion to defend. If evidence contradicts it, change the hypothesis.
  • The Pyramid Principle feels counterintuitive: People naturally want to tell the story chronologically (problem → analysis → conclusion). Audiences want the answer FIRST, then the supporting evidence. Lead with the recommendation.
  • Structured ≠ slow: Spending 30 minutes structuring the problem saves hours of unfocused analysis. The structure IS the speed.
  • Know when to stop: Analysis has diminishing returns. If you have enough evidence to make a confident recommendation, stop analyzing and recommend.

References

  • For issue tree templates by problem type, see references/issue-tree-templates.md
  • For Pyramid Principle writing guide, see references/pyramid-principle.md

How to use it

Copy the folder

Take asgard-ai-platform/meta-structured-problem from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.