Detect cognitive and statistical biases in text or data.
npx skills add https://github.com/inbharatai/claude-skills --skill bias-detector
Please help me install this Agent Skill. Skill: bias-detector Source: https://github.com/inbharatai/claude-skills/tree/main/skills/bias-detector Command: npx skills add https://github.com/inbharatai/claude-skills --skill bias-detector
This Skill helps identify and mitigate various cognitive and statistical biases in information, arguments, and data, leading to more objective and sound decision-making.
Analyze the following text for potential biases: "The new policy was a complete success because all the people I spoke to loved it."
High-intent search queries and answers about installing and using this skill.
To detect cognitive bias and logical fallacies in a text, you analyze the provided information for common heuristics like confirmation bias, survivorship bias, and sampling issues. This critical evaluation flags potential biases that might skew interpretation and supports objective decision-making.
Survivorship bias is a statistical bias where only successful cases are visible, skewing research analysis by ignoring failures. Detecting it requires critically evaluating information sources to ensure all data samples are accounted for, leading to more objective decision-making.
You check for confirmation bias and sampling issues by critically evaluating your arguments against common cognitive heuristics. Identifying whether your text selectively presents data or relies on flawed samples helps mitigate statistical biases and ensures sound decision-making.
Yes, you can evaluate news articles for logical fallacies by critically reviewing the information sources. The process detects biases such as confirmation bias and survivorship bias, flagging potential issues that might skew the interpretation of the presented information.
Identifying cognitive heuristics in data requires an understanding of common logical fallacies and cognitive heuristics. This foundational knowledge allows you to critically evaluate information sources and accurately detect biases like confirmation bias and sampling issues.
The main limitation of bias detection in arguments is that it requires a pre-existing understanding of common logical fallacies and cognitive heuristics. The analysis supports critical evaluation but relies on recognizing specific statistical biases like sampling issues within the provided text.
danielmiesslerAnalyze data-level biases, source conflicts, and journalism distortions in URLs, files, or text.
LuizEduPPEvaluate scientific claims for methodological rigor and bias.
goldengrapeApply a six-step framework to dissect arguments and detect biases.
mqzkimValidate trading strategy backtests for biases and statistical significance.
