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Knowledge Explainer

Education Updated 2026.08.29

Paste the following prompt into your AI chat to install this skill:

Please install @user_e02e04b8/knowledge-explainer into your AI assistant according to https://skillhub.cn/install/skillhub.md.

About this skill

Problem

Knowledge Explainer is aimed at education and learning conversations, where a model may answer correctly but present knowledge in a way that is hard to study from or teach. It focuses on knowledge explanation, asking the model to organize an answer around a concept, term, or learning point rather than only returning a conclusion.

How It Works

Once loaded as a model skill, it can be used in education-focused prompts:
- Provide a concept, term, formula, process, or difficulty to explain;
- The model structures the response as an explanatory answer, such as definition, interpretation, context, and caveats;
- This makes @user_e02e04b8/knowledge-explainer useful when the task needs clear instruction-like explanation rather than plain retrieval.

Boundaries

The skill is closer to teaching explanation than to a question bank, LMS, or certification tool. If a task requires citing a textbook edition, generating exams, grading assignments, or tracking learner progress, additional sources or external tools are needed. Always verify the knowledge source, especially for high-risk topics such as safety, medical, or legal content.

Use Cases

  • Explain the role of a token in API authentication to interns, splitting it into definition, context, and pitfalls.
  • Answer a student’s question about database indexes by organizing what it is, why it exists, and how it is used.
  • Prepare teaching notes that make machine-learning overfitting understandable to students.
  • Help a new engineer interpret code review feedback by clarifying terminology and engineering context.

Best For

  • Technical mentors who need to explain API authentication flows to interns
  • Computer-science teachers who need to write database-index explanations into lecture notes
  • Algorithm instructors who need to explain overfitting to students
  • Open-source maintainers who need to help independent learners understand engineering terminology