fallacy-detector

name	fallacy-detector
description	Use when someone presents a chain of reasoning or a story explaining why something happened, and the logic may have a structural flaw or the narrative may be too tidy. Covers logical fallacies (false dichotomy, post hoc, straw man) and narrative...
scenarios	["Check my reasoning for logical holes","This explanation feels too neat — is it a narrative fallacy?","They said 'if we do X then Y will happen' — is that valid?","이 논리에 오류가 있는지 봐줘","이 설명이 너무 깔끔한 것 같아, 확인해줘","이 주장의 구조가 맞는지 분석해줘"]
compatibility	{"recommended":["think-tool"],"optional":["sequential-thinking"],"remote_mcp_note":"think-tool이 있으면 논리적 오류와 서사 오류를 체계적으로 스캔하고 핵심 문제를 정밀하게 짚어낼 수 있습니다. Claude 설정 → MCP Servers에서 remote SSE 엔드포인트를 추가하세요."}

Fallacy Detector

When to Use / When Not to Use

Use when:

• An argument has a conclusion that needs testing before you act on it
• Someone is explaining why something happened and the story sounds too clean
• A debate or persuasion attempt needs structural analysis

Not for:

• Diagnosing why someone reasons poorly (use bias-auditor)
• Calibrating confidence levels (use epistemic-reasoner)

Process

Step 1 — State the argument or story. Confirm the core claim being analyzed.

Step 2 — Scan for logical fallacies. Flag only what's actually present.

Category	Fallacies
Structural	False dichotomy, slippery slope, circular reasoning, straw man
Authority/Social	Ad hominem, appeal to authority, bandwagon
Causation	Post hoc ergo propter hoc, cum hoc, hasty generalization

Step 3 — Scan for narrative fallacy. Separate scan — check for:

• Hindsight coherence: outcome sounds inevitable in retrospect
• Single-cause attribution: complex event explained by one clean cause
• Character-driven causation: traits driving outcome, ignoring systemic/situational forces
• Omission of counterfactual: similar cases with different outcomes ignored
• Emotional arc: events map too cleanly onto a satisfying story shape

Step 4 — Deliver the analysis. If no fallacies are present, say so.

Output Template

논리적 오류 / Logical Fallacies Detected:

[Fallacy name]: [Where it appears in the argument, specifically]
Why this matters: [What it invalidates or weakens in the conclusion]

서사 오류 / Narrative Fallacy Assessment:
[Present or absent. If present: which element of the story appears constructed rather than accurate]

핵심 문제 / Core Issue:
[The single most damaging error — the one that most undermines the argument's validity]

What Claude Does / What You Do

Claude	You
Scans systematically across fallacy categories	Provide the argument or explanatory story
Names only fallacies that are actually present	Confirm whether the identified pattern applies
Explains why each fallacy undermines the conclusion	Decide whether to revise, discard, or defend the argument
Runs a separate narrative fallacy scan on explanatory stories	Update your reasoning based on the structural findings

Key constraint: Naming a fallacy without explaining which step is unjustified and why is taxonomy, not analysis.

Related Skills

• bias-auditor — for cognitive biases rather than argument structure
• epistemic-reasoner — for calibrating confidence to evidence
• assumption-extractor — for surfacing hidden premises beneath arguments