robolearn

Creates assessments with varied question types (MCQ, code-completion, debugging, projects) aligned to learning objectives with meaningful distractors based on common misconceptions. Activate when educators design quizzes, exams, or tests measuring understanding; need questions at appropriate cognitive levels (Bloom's taxonomy); want balanced cognitive distribution (60%+ non-recall); or require rubrics for open-ended questions. Generates MCQs with diagnostic distractors, code-writing prompts, debugging challenges, and project-based assessments targeting deep understanding.

Integrate OpenAI ChatKit framework with custom backend and AI agents. Handles ChatKit server implementation, React component integration, context injection, and conversation persistence.

This skill should be used when scaffolding complex concepts for learners. It applies cognitive load architecture principles to break down concepts into digestible pieces while respecting learning science limits.

Docusaurus file naming, syntax, and structure conventions for RoboLearn platform

This skill should be used when deploying a Docusaurus site to GitHub Pages. It automates the configuration, building, and deployment process, handling GitHub Pages setup, environment configuration, and CI/CD automation. Includes local validation before GitHub Actions triggering.

Design simulation worlds using SDF with ground planes, models, physics configuration, and lighting

Generate measurable learning outcomes aligned with Bloom's taxonomy and CEFR proficiency levels for educational content. Use this skill when educators need to define what students will achieve, create learning objectives for curriculum planning, or ensure objectives are specific and testable rather than vague. This skill helps break down complex topics into progressively building learning goals with clear assessment methods and success criteria.

Generate lesson content following 4-Layer Teaching Framework with standardized metadata and Docusaurus conventions

Generate Mermaid diagrams for educational content. Use when visualizing concepts, architectures, or workflows.

This skill should be used when generating pedagogically-aligned slide decks from educational content using NotebookLM. It addresses the convergence toward generic, text-heavy slides by providing structured prompts that create engaging, proficiency-appropriate presentations aligned with specific educational frameworks.

Create browser-based Python exercises using Pyodide. Use for interactive coding without local setup.

ALWAYS generate interactive quizzes using the Quiz component (50 comprehensive questions total). Generates 50 college-level conceptual questions with immediate feedback per question. Quiz component automatically displays 15-20 questions per batch, randomized each retake. Features: immediate feedback after each answer (correct option + explanation + why wrong if incorrect), automatic batch shuffling on retake, no passing/failing threshold, color-coded feedback, theme support. Globally-registered Quiz component handles all UI/UX. Follows ##_chapter_##_quiz.md naming convention. INCLUDES: Automated answer redistribution with intelligent explanation regeneration (consolidates quiz-answer-redistributor functionality).

Generate ROS 2 custom message (.msg) and service (.srv) interface definitions for educational content. This skill should be used when creating lessons that teach interface design, writing exercises involving custom data types, or generating worked examples for robotics communication protocols.

Configure ros_gz_bridge to connect Gazebo topics with ROS 2 for closed-loop control

Generate ROS 2 Python launch files and multi-node system configurations for educational content. This skill should be used when creating lessons that teach launch file syntax, writing exercises involving multi-node startup, parameter configuration, or generating worked examples for robot system deployment.

Generate ROS 2 publisher and subscriber code examples for educational content. This skill should be used when creating lessons that teach ROS 2 pub/sub patterns, writing exercises involving topic-based communication, or generating worked examples for rclpy nodes.

Generate ROS 2 service server and client code examples for educational content. This skill should be used when creating lessons that teach request/response communication, writing exercises involving services, or generating worked examples for synchronous robot commands.

Configure camera, LIDAR, IMU, and contact sensors on simulated robots in Gazebo

This skill should be used when generating lesson summaries for educational content. It extracts key concepts, mental models, patterns, and common mistakes from lesson markdown files using a Socratic extraction process. Use this skill when a lesson file needs a `.summary.md` companion file, or when reviewing/refreshing existing summaries.

Create robot models using URDF with proper links, joints, visual geometry, collision shapes, and physical properties

Translate educational content to Urdu while preserving technical accuracy. Use for multilingual content delivery.

This skill should be used when creating visual assets for educational content. It provides professional creative brief methodology to activate reasoning mode for distinctive, pedagogically effective visuals.