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Skill190 estrellas del repoactualizado 14d ago

matlab-create-mcq-practice

Use when creating, asking, grading, or explaining multiple choice questions for MATLAB programming practice, concept checks, quizzes, or tutoring exercises.

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git clone --depth 1 https://github.com/matlab/agent-skills-playground /tmp/matlab-create-mcq-practice && cp -r /tmp/matlab-create-mcq-practice/demos/ai-tutoring/skills/matlab-create-mcq-practice ~/.claude/skills/matlab-create-mcq-practice
Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

SKILL.md

# MATLAB MCQ Practice

## Purpose

Create interactive multiple choice questions that test MATLAB understanding
through prediction, interpretation, debugging, and transfer. Use with
`matlab-tutor-learners` and `matlab-coach-programming`.

For instructors, MCQs are useful when they diagnose a misconception, not just
when they check recall. A strong MATLAB MCQ should reveal how the learner thinks
about arrays, indexing, operator behavior, types, or control flow.

## Question Design

Each question must include:

- A clear learning objective.
- A small MATLAB code snippet or concrete scenario when possible.
- Four answer choices labeled A-D.
- One best answer.
- Distractors based on plausible MATLAB misconceptions.
- Feedback for each option.
- A follow-up prompt that adapts to the learner's answer.

## Interaction Rule

When actively tutoring, ask one MCQ and wait for the learner's answer before
revealing the answer. Do not include the answer key unless the user asks to
generate a quiz artifact instead of running a session.

An MCQ answer key is an authoritative claim about MATLAB behavior.
When a MATLAB session is available, verify each code snippet and its correct
answer by running it before asserting the key or marking a learner wrong; when
no session is available, keep snippets simple enough that the behavior is
certain, and say so if it is not.

## MATLAB Misconception Bank

Use distractors based on:

- Confusing `*` with `.*`, `/` with `./`, or `^` with `.^`.
- Expecting zero-based indexing instead of one-based indexing.
- Confusing row and column vectors.
- Misunderstanding table variable indexing: `T.Var`, `T(:, "Var")`, `T{:, "Var"}`.
- Assuming strings and character vectors behave identically.
- Forgetting that assignment does not display output when suppressed by semicolon.
- Thinking `length` always means number of rows.
- Confusing logical indexing with numeric indexing.
- Expecting loops to be required where vectorized operations are clearer.
- Misreading function scope or workspace behavior.

## MCQ Template

Read [references/mcq-template.md](references/mcq-template.md) when generating a set of questions, a quiz, or a reusable question bank.

## Difficulty Levels

- **Novice**: syntax recognition, output prediction for one or two lines, indexing basics.
- **Developing**: code tracing, function behavior, tables, plotting, common errors.
- **Proficient**: debugging, vectorization tradeoffs, tests, floating-point behavior, data workflows.

## Grading Response Pattern

Use this after the learner answers:

```text
Correct/Not quite.
Why: [one MATLAB-specific explanation].
The tempting misconception is [misconception].
Try this follow-up: [one transfer question].
```

After a correct answer there is no held misconception; name the most tempting
distractor and why a learner might pick it instead.

## Instructor Adoption Notes

- Use MCQs before hands-on work to surface misconceptions quickly.
- Prefer code-prediction questions over vocabulary-only questions.
- Review which distractors students choose; those choices often point to the
  next mini-lesson or script exercise.
agent-skill-authorSkill

Use this skill when the user wants to author, design, scope, or refine an Agent Skill (a SKILL.md file). Trigger phrases include "build a new skill", "design an agent skill", "scope a SKILL.md", "how should I structure this skill", "write a skill for X", "my skill isn't working well", or any request to improve an existing SKILL.md. Walks the user through an empirical, test-first process — probe the agent for real failures, design only for genuine knowledge gaps, iterate against runnable examples, and verify across models.

embedded-ai-deploymentSkill

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matlab-apply-assignment-guardrailsSkill

Use when a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any programming task where academic integrity, course policy, or instructor constraints may limit direct solutions. Use to provide policy-aware hints, conceptual coaching, partial feedback, and assignment-safe MATLAB tutoring.

matlab-coach-debuggingSkill

Use when tutoring a learner through MATLAB debugging, error interpretation, failed tests, incorrect outputs, array-shape problems, indexing mistakes, function argument issues, or code repair practice. Use for guided debugging sessions, debugging drills, teach-the-agent critique, and evidence-based MATLAB troubleshooting.

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Use when an AI tutor session concerns MATLAB programming concepts, MATLAB syntax, MATLAB errors, MATLAB code style, MATLAB projects, or MATLAB toolbox workflows.

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Use when an instructor wants to create, interview for, configure, install, update, or review a course AI-use policy for MATLAB AI tutoring. Produces an AI-POLICY.md file for LMS sharing and local tutoring-session enforcement by assignment guardrails.

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Create MATLAB Course Designer MATLAB Exercise learning activities by wrapping the existing matlab-generate-grader-assessments skill, then validating generated solution.m, template.m, and tests.m files with MATLAB MCP Server tool calls. Use when the user asks to create a MATLAB Exercise, MATLAB course activity, Course Designer MATLAB activity, validated MATLAB solution file, or MATLAB Exercise component folder.

matlab-create-hands-on-exercisesSkill

Use when prompting a learner to complete hands-on MATLAB coding exercises, guided practice, debugging drills, code tracing, small MATLAB projects, or MATLAB-script assessment during tutoring. Use when the tutor should create a complete runnable MATLAB script, execute it through MATLAB tools, compare the produced outputs with expected outputs, and evaluate MATLAB programming style.