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rigorous-reasoning skill

/.claude/skills/rigorous-reasoning

This skill helps you analyze arguments and construct rigorous proofs using philosophical methods and formal reasoning to improve critical thinking.

npx playbooks add skill toilahuongg/shopify-agents-kit --skill rigorous-reasoning

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---
name: rigorous-reasoning
description: "Rigorous reasoning using philosophical theories and scientific methods. Use this skill when analyzing logic, evaluating arguments, constructing proofs, critiquing opinions, or solving complex problems requiring critical thinking. Triggers - debate, proof, critique, logical analysis, argument evaluation, fallacy detection, inference, argumentation, logical fallacy, critical thinking."
---

# Rigorous Reasoning

This skill provides a rigorous reasoning framework based on philosophy and scientific methods to analyze, evaluate, and construct arguments.

## Core Principles

### 1. Socratic Method

Ask continuous questions to clarify and challenge assumptions:

```
Clarifying definitions → Challenging assumptions → Questioning evidence → Exploring consequences → Considering alternatives
```

**Application:**
- "When you say X, how do you define X?"
- "What assumptions underlie this argument?"
- "What evidence supports this conclusion?"
- "If this is true, what are the logical consequences?"

### 2. Standard Argument Structure

Every argument must have:

```
PREMISES
  ├── Premise 1: [Verifiable claim]
  ├── Premise 2: [Verifiable claim]
  └── ...
           ↓
INFERENCE RULE
  └── [Modus ponens / Modus tollens / Syllogism / ...]
           ↓
CONCLUSION
  └── [Claim logically derived from premises]
```

### 3. Valid Inference Rules

| Rule | Form | Example |
|------|------|---------|
| **Modus Ponens** | P → Q, P ⊢ Q | If it rains, the road is wet. It rains. → The road is wet. |
| **Modus Tollens** | P → Q, ¬Q ⊢ ¬P | If it rains, the road is wet. The road is not wet. → It's not raining. |
| **Syllogism** | ∀x(P(x)→Q(x)), P(a) ⊢ Q(a) | All men are mortal. Socrates is a man. → Socrates is mortal. |
| **Disjunctive Syllogism** | P ∨ Q, ¬P ⊢ Q | Either A or B. Not A. → B. |
| **Hypothetical Syllogism** | P → Q, Q → R ⊢ P → R | If A then B. If B then C. → If A then C. |

## Identifying Logical Fallacies

### Formal Fallacies

| Fallacy | Description | Invalid Example |
|---------|-------------|-----------------|
| **Affirming the Consequent** | P→Q, Q ⊢ P (INVALID) | If rain, then wet. Wet → Rain (INVALID: could be other causes) |
| **Denying the Antecedent** | P→Q, ¬P ⊢ ¬Q (INVALID) | If study hard, then pass. Don't study hard → Don't pass (INVALID) |

### Informal Fallacies

| Fallacy | Description | How to Identify |
|---------|-------------|-----------------|
| **Ad Hominem** | Attacking the person instead of the argument | "He's wrong because he's X" |
| **Straw Man** | Distorting opponent's argument | Compare with original argument |
| **Appeal to Authority** | Citing irrelevant authority | Is the expert qualified in this field? |
| **False Dichotomy** | Presenting only 2 options when more exist | Is there a third option? |
| **Slippery Slope** | Unproven chain of consequences | Is each step evidenced? |
| **Circular Reasoning** | Conclusion embedded in premises | Are premises independent? |
| **Post Hoc** | Confusing correlation with causation | Is there a causal mechanism? |
| **Hasty Generalization** | Concluding from small sample | Is the sample representative? |
| **Appeal to Emotion** | Using emotion instead of logic | Separate emotion from argument |
| **Tu Quoque** | "You do it too" | Irrelevant to correctness |

## Scientific Method in Reasoning

### Claim Evaluation Process

```
1. OBSERVATION
   └── What claim needs evaluation?

2. HYPOTHESIS
   ├── H₀ (null): The claim is false
   └── H₁ (alternative): The claim is true

3. PREDICTION
   └── If H₁ is true, what do we expect to observe?

4. TESTING
   ├── Evidence supporting H₁?
   ├── Evidence refuting H₁?
   └── Is the evidence falsifiable?

5. CONCLUSION
   ├── Confidence level?
   └── Alternative hypotheses?
```

### Evidence Standards

**Evidence hierarchy (strongest to weakest):**

1. **Meta-analysis / Systematic review** - Synthesis of multiple studies
2. **Randomized Controlled Trial (RCT)** - Controlled experiments
3. **Cohort study** - Group follow-up research
4. **Case-control study** - Comparative case research
5. **Expert opinion** - Professional judgments
6. **Anecdotal evidence** - Personal stories (WEAKEST)

### Occam's Razor

> Among equivalent explanations, choose the simplest one.

**Application:**
- Don't multiply entities beyond necessity
- Prefer hypotheses with fewer assumptions
- Simple ≠ Correct, but it's a good starting point

### Falsifiability Principle (Karl Popper)

> A scientific claim must be capable of being refuted.

**Test:**
- "What evidence would prove this wrong?"
- If no answer → Not a scientific claim

## Argument Analysis Process

### Step 1: Reconstruction

```
Input: Raw argument
   ↓
1. Identify main conclusion
2. List explicit premises
3. Identify hidden premises
4. Arrange in logical structure
   ↓
Output: Standardized argument
```

### Step 2: Evaluate Premises

For each premise, ask:
- **True?** (Is there supporting evidence?)
- **Relevant?** (Does it connect to the conclusion?)
- **Sufficient?** (Is it strong enough to infer the conclusion?)

### Step 3: Evaluate Inference

- Does the inference follow valid rules?
- Are there any formal fallacies?
- Does the conclusion follow from the premises?

### Step 4: Consider Counterarguments

- Are there counterexamples?
- Are there stronger opposing arguments?
- Is there additional information that changes the conclusion?

## Thinking Tools

### Steel Man (Opposite of Straw Man)

Before critiquing, build the **strongest** version of the opposing argument:
1. Fully understand the opponent's position
2. Add reasonable premises they may have omitted
3. Rephrase in the most compelling way
4. Then critique

### Principle of Charity

When an argument can be interpreted multiple ways, choose the most reasonable interpretation before evaluating.

### Reductio ad Absurdum

Prove something false by:
1. Assume it's true
2. Derive logical consequences
3. Show consequences lead to contradiction
4. Conclude: The initial assumption is false

### Thought Experiment

Construct hypothetical scenarios to test intuitions and explore logical consequences.

## Quick Evaluation Checklist

When encountering an argument, check:

- [ ] Is the conclusion clearly stated?
- [ ] Are all premises listed?
- [ ] Do premises have supporting evidence?
- [ ] Does inference follow valid rules?
- [ ] No formal fallacies?
- [ ] No informal fallacies?
- [ ] Considered opposing viewpoints?
- [ ] Is the claim falsifiable?
- [ ] Is evidence strong enough?
- [ ] Applied Occam's Razor?

## Applied Example

### Analyzing an Argument

**Raw argument:** "AI will replace all jobs because computers are becoming increasingly intelligent."

**Reconstruction:**
```
P1: Computers are becoming increasingly intelligent
P2: [Hidden] All jobs can be performed by sufficiently intelligent machines
P3: [Hidden] This development will continue without limits
─────────────────────────────────
C: AI will replace all jobs
```

**Evaluation:**
- P1: Partially true, need to quantify "intelligent"
- P2: Unproven assumption - are there jobs requiring human elements?
- P3: Assumption about the future - are there physical/technical limits?
- **Fallacies:** Hasty Generalization, Slippery Slope
- **Conclusion:** Weak argument, needs stronger evidence for P2 and P3

## References

For deeper understanding of philosophical foundations, see [references/philosophical-frameworks.md](references/philosophical-frameworks.md) - including:
- Classical Logic (Aristotle)
- Rationalism (Descartes, Spinoza, Leibniz)
- Empiricism (Locke, Hume)
- Critical Philosophy (Kant)
- Logical Positivism (Vienna Circle)
- Philosophy of Science (Karl Popper)
- Dialectical Method (Hegel, Marx)
- Pragmatism (Peirce, James, Dewey)

Overview

This skill provides a rigorous reasoning framework combining philosophical methods and scientific practices to analyze, evaluate, and construct arguments. It is designed for use in debates, proofs, critique, and complex problem solving where clear inference, fallacy detection, and evidential standards matter. The goal is to produce transparent, reproducible judgments and stronger arguments.

How this skill works

The skill reconstructs raw arguments into premises, inference rules, and conclusions, then evaluates each premise for truth, relevance, and sufficiency. It checks inference validity against formal rules (e.g., modus ponens, syllogism), flags formal and informal fallacies, and applies the scientific claim-evaluation cycle (hypothesis, prediction, testing, conclusion). It also uses tools like steel-manning, reductio ad absurdum, and Occam's Razor to refine and stress-test positions.

When to use it

  • Evaluating the logical structure of an essay, speech, or policy claim
  • Testing the validity of proofs or formal arguments
  • Detecting and explaining logical fallacies in debates or media
  • Designing falsifiable hypotheses and evidence-based tests
  • Constructing well-supported positions for academic or technical writing

Best practices

  • Start by reconstructing the argument into explicit premises and the stated conclusion
  • Apply the principle of charity and steel-man the strongest opposing interpretation first
  • Separate empirical claims (require evidence) from conceptual claims (require definition)
  • Use the evidence hierarchy and ask what would falsify the claim
  • Document hidden premises and evaluate their plausibility before accepting conclusions

Example use cases

  • Turn a persuasive op-ed into a numbered premise-inference-conclusion form and identify weak links
  • Assess whether a scientific claim is falsifiable and recommend tests or data to collect
  • Analyze a debate transcript to locate ad hominem, straw man, or false dichotomy fallacies
  • Formalize a conjecture, list assumptions, and outline a reductio ad absurdum or counterexample strategy
  • Compare competing explanations and apply Occam's Razor to select the simplest viable hypothesis

FAQ

Can this skill handle both everyday arguments and formal proofs?

Yes. It adapts the same reconstruction-evaluate-test workflow: for informal arguments it emphasizes evidence and fallacy checks; for formal proofs it focuses on inference rules and validity.

How does it treat uncertain or probabilistic claims?

It asks for probabilistic evidence, assesses sample size and representativeness, and reports confidence levels rather than binary truth when claims rest on statistical or inductive support.