Learning

Identify logical fallacies in arguments

Identify the reasoning problem, quote the original sentence, and explain the implications, while avoiding casually labeling disagreements as fallacies.

Customize this prompt

Traceable sourceFabric · find_logical_fallacies ↗

Complete prompt

You are an argument analyst familiar with formal logic and informal fallacies. Please check the following:

Argument content: [Paste text]
Analysis depth: [Quick check/detailed analysis]

For each inference problem that does exist, output:
- Fallacy or problem name
- Corresponds to the original sentence
- Why this poses the problem
- How it affects the credibility of the conclusion
- How to rewrite to make the argument more rigorous

Later added:
1. A valid and strong part of the argument
2. Key premises that are omitted
3. Overall effectiveness evaluation

Note: The use of emotions, analogies, or authoritative opinions does not necessarily constitute a fallacy. Don't invalidate your reasoning just because you disagree with the conclusion; insufficient evidence and a false conclusion are two different things.

Example output

Problem: Appealing to popularity.
Original sentence: "It has the most users, so it must be the most secure software."
Explanation: The number of users does not directly prove security; the conclusion needs to be supported by evidence such as vulnerability records, audit results, and response mechanisms.

USAGE GUIDE

When to use it

Identify the reasoning problem, quote the original sentence, and explain the implications, while avoiding casually labeling disagreements as fallacies. Use it as a structured starting point, then review the result against your original material.

How to fill the variables

Paste text: Add concrete facts, context, and constraints. Mark unknown details instead of guessing.
Quick check/detailed analysis: Add concrete facts, context, and constraints. Mark unknown details instead of guessing.

Get better results

Describe the audience and intended decision.
Include source material and hard constraints.
State what the model must not invent.

Before you use the output

Verify facts, numbers, and quotations.
Check that uncertainty is clearly labeled.
Test or review high-impact recommendations.

Editorial note: This template has been structured for practical use. Results vary by model and input; verify important outputs against primary sources.