10. Education & Learning

Creates dynamic, randomized 50-question quizzes with immediate feedback for end-of-chapter assessments, displaying 15-20 questions per session.

Provides domain-specific configuration profiles for creating learning resources, adapting search strategies, terminology, and content structures across academic domains like technology and history.

Generates educational assessments with diverse question types (MCQ, coding, debugging) aligned to learning objectives and Bloom's taxonomy, featuring diagnostic distractors and rubrics.

Displays the current status of the knowledge base and provides an overview of recent learnings for the user.

Clears the AI's internal knowledge base to enable a fresh start in educational or conversational learning tasks.

Assists HSK4 learners in achieving native-like fluency through contextual expression analysis, essay refinement, and real-world example sourcing.

Explains complex code to team members in clear, understandable terms for effective knowledge sharing.

Immersive cave exploration simulation revealing bioluminescent crystals, underground water sources, and ancient traces.

Creates progressive learning pathways by deconstructing complex topics into manageable steps with optimized cognitive load for educational content.

Guides users through contributing a developed skill to an upstream repository via Git branching, committing, pushing, and creating a pull request.

Validates Python, Node, and Rust code examples in educational book chapters using the 4-Layer Teaching Method, ensuring accuracy for learning materials.

Generates learner profiles via conversational interviews for educational assessment, used by the project-interviewer agent during initialization.

Provides a systematic rubric for evaluating educational content quality across six weighted categories including technical accuracy and pedagogical effectiveness.

Analyzes meeting transcripts to deliver actionable communication feedback, enhancing leadership and interpersonal skills for professional growth.

Provides expert tutorials and best practices for migrating Logseq graphs from Markdown to Database format, including strategies and issue resolution.

Maps skills to proficiency levels using CEFR, Bloom's taxonomy, and DigComp frameworks for designing skill progressions and assessing learner proficiency.

Analyzes coding patterns from chat history, identifies development gaps, and delivers personalized learning resources via Slack to enhance developer growth.

Guides users through creating and validating Agent Skills with proper structure, design patterns, and SKILL.md/verify.py implementation.

Guides users through creating Claude Code skills by explaining structure, naming, descriptions, and progressive disclosure best practices.

Provides actionable recommendations and step-by-step guidance for achieving goals or resolving problems based on user queries.

Teaches best practices for creating Claude Code skills, including naming conventions, file structure, and project organization.

Designs evidence-based practice exercises using cognitive science principles to enhance learning retention and skill development for educational purposes.

Provides project-agnostic guidance for AI assistants using Chronicle, including search-first directives and best practices for workflow patterns across all tracked projects.

Automates Google NotebookLM to create educational content including podcasts, videos, and quizzes from research sources.