Audit and rewrite multiple-choice questions for knowledge mapping domains.
npx skills add https://github.com/ContextLab/mapper --skill audit-questions
Please help me install this Agent Skill. Skill: audit-questions Source: https://github.com/ContextLab/mapper/tree/main/.claude/skills/audit-questions Command: npx skills add https://github.com/ContextLab/mapper --skill audit-questions
This Skill systematically audits and improves the quality of multiple-choice questions used in knowledge mapping applications, ensuring they accurately test conceptual understanding rather than trivia or recognition.
Use the audit-questions skill to audit questions for the biology domain.
High-intent search queries and answers about installing and using this skill.
Auditing multiple-choice questions involves detecting quality issues like weak distractors, guessability, and keyword leakage, then iteratively rewriting the flagged questions until they meet strict standards for testing conceptual understanding.
Recognition testing occurs when questions assess trivia identification rather than conceptual understanding. You eliminate it by auditing questions for definition-based formats and excessive length, then rewriting them to evaluate deeper knowledge application.
To automatically rewrite poorly phrased questions for knowledge mapping, you run an iterative quality audit that accepts a domain name, flags structural flaws like cultural bias, and generates revised questions meeting strict difficulty criteria.
Yes, an automated question quality audit can process large sets of physics or biology questions by systematically identifying poorly phrased items and rewriting them into more effective learning tools for knowledge mapping.
Common multiple-choice question flaws compromising knowledge mapping include excessive length, recognition testing, weak distractors, guessable answers, keyword leakage, cultural bias, and definition-as-question formats.
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