本文へ移動
cccskills
無料GitHub で公開

matlab-create-course-activity

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.

インストール方法を見る

含まれるファイル(4)

  • SKILL.md8.9 KB
  • references/course-designer-artifacts.md4.5 KB
  • references/grader-wrapper-workflow.md1.7 KB
  • references/matlab-validation-rules.md2.7 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

MATLAB Course Activity Generator

Create MATLAB Course Designer-ready MATLAB Exercise learning activities. This skill is a wrapper around the existing matlab-generate-grader-assessments skill: use matlab-generate-grader-assessments first to create the shared MATLAB Grader-style component parts, then use MATLAB MCP Server tool calls to validate the generated MATLAB files and add Course Designer authoring metadata.

Input

The user may have provided a module objective or activity idea in their request. If it is missing or too vague, collect missing activity inputs in Step 1.

Reference Files

Read these references from the references/ directory as needed:

  • references/grader-wrapper-workflow.md — how to call and use matlab-generate-grader-assessments
  • references/matlab-validation-rules.md — MATLAB MCP validation workflow
  • references/course-designer-artifacts.md — output folder and metadata rules

Read references/grader-wrapper-workflow.md and references/course-designer-artifacts.md before creating artifacts.

Required Tooling

Use the existing matlab-generate-grader-assessments skill for the initial component generation. Use MATLAB MCP Server calls for validation:

  • detect_matlab_toolboxes for product/toolbox availability
  • check_matlab_code for static analysis of .m files
  • run_matlab_file for runnable scripts, validation drivers, or test harnesses
  • evaluate_matlab_code for targeted checks, path setup, function calls, and MATLAB Exercise test smoke checks

Do not claim a MATLAB Exercise is ready unless the generated MATLAB files have been checked through MATLAB MCP calls or the final output clearly marks validation as partial.

Pipeline Overview

Step 1: Collect activity inputs and Course Designer placement
Step 2: Invoke grader for shared MATLAB Exercise component parts
Step 3: Split description.txt into background.m and task.m
Step 4: Add Course Designer-only authoring fields
Step 5: Validate solution.m, template.m, and tests.m with MATLAB MCP calls
Step 6: Write Course Designer-ready activity metadata and review notes

Step 1: Activity Inputs

Collect only missing information:

  • Course title or course identifier
  • Module title and module order
  • Learning activity title and activity order
  • Module objective and observable learner outcome
  • MATLAB concept: script, function, class, object usage, data analysis, visualization, numerical methods, app workflow, or another domain
  • Assessment purpose: formative, summative, or both
  • Required MATLAB and toolbox products
  • Starter/template expectations
  • Solution behavior
  • Validation requirements
  • Output directory

Default to a Course Designer learning activity type of MATLAB Exercise.

Step 2: Invoke matlab-generate-grader-assessments

Use references/grader-wrapper-workflow.md.

Call or prompt the existing matlab-generate-grader-assessments skill before creating Course Designer metadata. The expected matlab-generate-grader-assessments output is:

  • description.txt
  • template.m
  • solution.m
  • tests.m
  • function_call.m (Function assessment items)
  • supporting_class.m (Object usage assessment items)

Store the matlab-generate-grader-assessments output under:

grader-items/module-NN-activity-MM-[slug]/

[slug] is the assessment item's snake_case title with underscores replaced by hyphens. This wrapper placement overrides the generator's standalone {snake_title}/ folder rule.

Do not hand-write these files first. If matlab-generate-grader-assessments is unavailable, stop and report that MATLAB Exercise generation is blocked unless the user explicitly accepts a planning-only fallback.

Step 3: Split Description for Course Designer

Create two plaintext .m files from description.txt for copy/paste into the MATLAB Course Designer web application:

Per the MATLAB Course Designer documentation for creating MATLAB Exercises: https://www.mathworks.com/help/matlab-and-simulink-online-courses/ug/create-matlab-exercise-using-matlab-course-designer.html

  • The Background field sets the context for the task, explains the learning objective, and provides high-level information learners need to complete the task.
  • The Task field provides the instructions learners follow to complete the task, including specific instructions such as which functions or variable names to use.

Treat background.m and task.m as plain-text field transport files, not executable MATLAB scripts. Preserve the text exactly as it should be pasted into Course Designer. Do not prefix prose with % solely to make the files valid MATLAB code.

Split workflow:

  1. Read description.txt once and mark each paragraph as context, objective, prerequisite, instruction, deliverable, constraint, self-check, or grading detail.
  2. Put only context, purpose, learning objective, and necessary high-level prerequisite information in background.m.
  3. Put concrete learner instructions, ordered task steps, deliverables, required variable/function/file names, constraints, expected outputs, and self-check prompts in task.m.
  4. Move implementation details out of background.m and into task.m.
  5. Move broad conceptual exposition out of task.m unless it is needed to understand a specific instruction.
  6. If description.txt has no clear boundary, create a concise background from the opening context and put the full actionable prompt in task.m.
  7. Keep hidden-test details, reference solution details, and grading mechanics out of both files unless they are intentionally learner-facing.
  8. Do not modify the original description.txt; keep it in the matlab-generate-grader-assessments source folder.

Quality check:

  • background.m should still make sense if read before seeing the task steps.
  • task.m should be actionable without duplicating the full background.
  • Both files should be ready to paste into Course Designer text fields without cleanup.

Step 4: Add Course Designer Fields

Create the Course Designer MATLAB Exercise activity from the matlab-generate-grader-assessments output. Add fields that are needed by MATLAB Course Designer but not generated by the first-pass component workflow:

  • background.m and task.m copy/paste fields
  • Module placement and learning activity order
  • Estimated time
  • Prerequisite context
  • Required products and toolboxes
  • Learner setup notes
  • Course Designer persistence notes
  • Optional Common Cartridge placement notes

Step 5: Validate MATLAB Files

Use references/matlab-validation-rules.md.

At minimum:

  • Confirm solution.m, template.m, and tests.m exist.
  • Run check_matlab_code on solution.m, template.m, and tests.m only. background.m and task.m are plain-text copy/paste fields, not valid MATLAB code, and must not be linted.
  • Execute or smoke-test solution.m when runnable.
  • Validate tests.m syntax and MATLAB Exercise assess calls where possible.
  • Confirm the learner template preserves the expected names and scaffold.
  • Write all results to validation-report.md.

When execution is not possible because the generated item requires MATLAB Grader runtime functions, run static checks and targeted syntax checks, then mark runtime validation as partial.

Step 6: Course Designer Activity Artifacts

Use references/course-designer-artifacts.md.

Write these files in the activity folder:

  • activity.md
  • background.m
  • task.m
  • instructor-notes.md
  • validation-report.md
  • course-designer-activity.json
  • grader-source.md, the reference file that maps the activity to its grader-items/ source folder and component files (see references/course-designer-artifacts.md)

The course-designer-activity.json file is the import-oriented sidecar for future Course Designer API work. It must include course, module, learning activity, background.m, task.m, MATLAB file, product, validation, and matlab-generate-grader-assessments source metadata.

Output Rules

  • The final answer must list the activity folder, matlab-generate-grader-assessments source folder, metadata path, and validation report path.
  • Do not claim validation passed unless the MATLAB MCP checks passed.
  • If validation is partial, state exactly which checks were deferred.
  • Preserve the Course Designer hierarchy: course -> module -> learning activity.
  • Keep the matlab-generate-grader-assessments output intact and record any Course Designer-only additions separately.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

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.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/agent-skills-playground1842026年10月10日 更新

Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or 3P-imported models rebuilt as dlnetwork for lean hardware (Cortex-M, DSP), (2) direct C/C++ code generation from PyTorch and LiteRT models for high-performance hardware (Cortex-A, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU/DSP; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, importNetworkFromPyTorch, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/agent-skills-playground1842026年10月10日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/agent-skills-playground1842026年10月10日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/agent-skills-playground1842026年10月10日 更新

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

日本語の概要は準備中です。原文の説明を表示しています。

matlab/agent-skills-playground1842026年10月10日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/agent-skills-playground1842026年10月10日 更新

matlab のスキルをすべて見る

このスキルの問題を報告する