find-fallacies_skill

This skill analyzes text to identify logical fallacies, names them, locates where they appear, and explains why they are invalid.
  • TypeScript

0

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill nweii/agent-stuff --skill find-fallacies

  • changelog.md201 B
  • SKILL.md3.9 KB

Overview

This skill analyzes text to identify logical fallacies and explain why each instance is flawed. It flags formal and informal errors in reasoning, locates them in the text, and gives a concise explanation so you can revise arguments or evaluate claims more critically. Use it when reviewing debates, essays, articles, or policy arguments.

How this skill works

The skill scans provided text for common formal and informal fallacies drawn from a comprehensive reference list. For each detected fallacy it reports the fallacy name and type, cites where it appears (quote or location), and gives a brief explanation of why that passage is fallacious. If no fallacies are detected, it highlights where reasoning is sound and what supports the claims.

When to use it

  • Reviewing op-eds, blog posts, or news articles for flawed reasoning
  • Preparing debate rebuttals or critique notes for presentations
  • Auditing research summaries or policy proposals for hidden assumptions
  • Teaching critical thinking or logic with real-world examples
  • Evaluating social media arguments or comment threads for misleading claims

Best practices

  • Provide the full passage or clear excerpts so fallacies can be located precisely
  • State whether you want shallow detection (common fallacies) or deep analysis (subtle formal errors)
  • Use findings to revise premises and evidence rather than only criticizing tone
  • Combine this analysis with fact-checking for stronger evaluations
  • Ask for prioritized issues when text is long to focus on highest-impact errors

Example use cases

  • Identify straw man, ad hominem, or appeal-to-authority in an op-ed before publishing a response
  • Spot correlation-vs-causation and post hoc errors in a policy brief to improve recommendations
  • Teach students to recognize false dilemmas and slippery slopes in political rhetoric
  • Audit a company blog for cherry picking or survivorship bias in success stories
  • Evaluate debate transcripts to extract key logical errors for coaching

FAQ

It detects many common and formal fallacies reliably, but subtle or context-dependent errors sometimes require human judgment and domain knowledge.

What output format does it use?

It returns a concise list of fallacies with the name, type, location in the text, and a brief explanation of why each is fallacious.

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