Does this skill detect logical fallacies?

Yes, it examines argument structures to identify logical fallacies, circular reasoning, and unstated hidden assumptions.

Can it help with academic or scientific research?

Absolutely. It can critique research designs, assess internal and external validity, and evaluate the statistical rigor of methodology.

How does it assess the strength of evidence?

It evaluates source authority, the type of evidence provided, and the strength of the connection between the evidence and the claims being made.

What kind of output report does it provide?

The skill generates a comprehensive report including claim mapping, an evidence assessment table, bias concerns, and an overall strength rating with recommendations.

What types of content can the Analyze skill evaluate?

You can provide the skill with direct text, URLs to web content, references to specific research papers, or individual argumentative claims for evaluation.

Critical Analysis & Research

Name: Critical Analysis & Research
Author: poemswe

bypoemswe

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Data Science & ML

Conducts rigorous evaluations of claims, evidence, and logical arguments to detect bias and validate research methodologies.

About

The Analyze skill for Claude Code is a sophisticated research utility designed to deconstruct and evaluate complex arguments, scientific papers, and textual claims. By systematically assessing source credibility, logical validity, and potential cognitive biases, it provides users with a comprehensive breakdown of information strength. This skill is particularly valuable for developers, researchers, and decision-makers who need to filter misinformation, identify flawed methodologies, or perform deep-dive critiques of technical documentation and industry whitepapers.

Key Features

Logical Fallacy & Hidden Assumption Detection
Methodology & Statistical Rigor Critique
Alternative Hypothesis & Explanation Generation
2 GitHub stars
Cognitive and Research Bias Identification
Evidence Quality & Source Credibility Assessment

Use Cases

Verifying the technical claims of a new library or software framework.
Identifying logical flaws or hidden biases in project proposals and arguments.
Critically reviewing academic papers or technical research documents.

About

Key Features

Logical Fallacy & Hidden Assumption Detection
Methodology & Statistical Rigor Critique
Alternative Hypothesis & Explanation Generation
2 GitHub stars
Cognitive and Research Bias Identification
Evidence Quality & Source Credibility Assessment

Use Cases

Verifying the technical claims of a new library or software framework.
Identifying logical flaws or hidden biases in project proposals and arguments.
Critically reviewing academic papers or technical research documents.