Meta Mental Models

---
name: "meta-mental-models"
description: "Apply a latticework of mental models from multiple disciplines to improve decision quality. Use this skill when the user needs to think more clearly, avoid cognitive blind spots, apply cross-disciplinary reasoning, or evaluate a complex decision from multiple angles — even if they say 'how should I think about this', 'what am I missing', 'give me a different perspective', or 'what frameworks apply here'."
metadata:
  category: "WP-22 跨學科"
  tags: ["meta-thinking", "mental-models", "munger", "decision-making"]
---

# Mental Models Toolkit

## Framework

```
IRON LAW: Use Multiple Models, Not Just Your Favorite

"To a man with a hammer, everything looks like a nail." (Munger)
A single mental model creates blind spots. Apply 2-3 models from
DIFFERENT disciplines to any important decision. Where models agree,
confidence is high. Where they disagree, the disagreement reveals
the most important dimension of the decision.
```

### Core Mental Models (Cross-Disciplinary)

**From Physics/Engineering**
| Model | Principle | Application |
|-------|-----------|------------|
| **Inversion** | Instead of "how do I succeed?", ask "how would I fail?" Then avoid that. | Risk management, pre-mortem |
| **Second-order effects** | Every action has consequences, which have consequences. Think two steps ahead. | Policy design, strategy |
| **Entropy** | Systems tend toward disorder without energy input. Things decay by default. | Maintenance, quality, relationships |

**From Biology**
| Model | Principle | Application |
|-------|-----------|------------|
| **Evolution/natural selection** | What survives is what's adapted, not what's "best" in absolute terms. | Market competition, product-market fit |
| **Red Queen effect** | You must keep improving just to stay in the same place (because competitors improve too). | Competitive strategy |
| **Niche specialization** | Generalists and specialists coexist because they serve different niches. | Market positioning, career strategy |

**From Mathematics/Statistics**
| Model | Principle | Application |
|-------|-----------|------------|
| **Pareto principle (80/20)** | ~80% of effects come from ~20% of causes. | Prioritization, resource allocation |
| **Regression to the mean** | Extreme results tend to be followed by more average ones. | Performance evaluation, forecasting |
| **Bayes' theorem** | Update beliefs based on new evidence, weighted by prior probability. | Decision-making under uncertainty |

**From Psychology**
| Model | Principle | Application |
|-------|-----------|------------|
| **Incentive-caused bias** | People do what they're incentivized to do, not what you ask them to do. | Compensation design, policy design |
| **Circle of competence** | Know what you know and what you don't. Stay within your expertise for high-stakes decisions. | Self-awareness, delegation |
| **Hanlon's razor** | Never attribute to malice what is adequately explained by ignorance or incompetence. | Conflict resolution, workplace dynamics |

### Application Method

1. **State the decision or problem**
2. **Select 2-3 relevant models** from different disciplines
3. **Apply each model** to the situation — what does it suggest?
4. **Compare conclusions** — where do they agree? Where do they disagree?
5. **Synthesize** — the disagreement reveals the key trade-off to resolve

## Output Format

```markdown
# Multi-Model Analysis: {Decision}

## Models Applied
| Model | Discipline | Insight |
|-------|-----------|---------|
| {model 1} | {field} | {what this model says about the situation} |
| {model 2} | {field} | {what this model says} |
| {model 3} | {field} | {what this model says} |

## Convergence
{Where models agree — high confidence}

## Divergence
{Where models disagree — key trade-off to resolve}

## Synthesis
{Recommended decision based on multi-model analysis}
```

## Gotchas

- **Models are simplifications**: Every model omits something. The map is not the territory. Use models as lenses, not as truth.
- **Model inventory grows over time**: Start with 10-15 core models. Add new ones as you encounter new domains. Quality of application matters more than quantity of models.
- **Some models conflict by design**: Inversion says "avoid failure." Evolution says "failure is how you learn." The conflict is resolved by context: avoid catastrophic failure, embrace recoverable failure.
- **Don't force-fit**: Not every model applies to every situation. If a model doesn't naturally illuminate the problem, skip it — don't stretch it to fit.

## References

- For expanded mental models catalog (50+), see `references/mental-models-catalog.md`