matlab-apply-assignmen…
Use when a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any programming task where academic…
Create MATLAB Course Designer Simulink Exercise learning activities with starter and solution Simulink model files. Use when the user asks to create a Simulink activity, Simulink Exercise, starter model, solution model, model-based learning activity, or Course Designer-ready
$ npx -y skills add matlab/agent-skills-playground --skill simulink-create-course-activity --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/simulink-create-course-activityContext preview
The summary Claude sees to decide when to auto-load this skill.
Create MATLAB Course Designer Simulink Exercise learning activities with starter and solution Simulink model files. Use when the user asks to create a Simulink activity, Simulink Exercise, starter model, solution model, model-based learning activity, or Course Designer-ready
name: simulink-create-course-activity description: Create MATLAB Course Designer Simulink Exercise learning activities with starter and solution Simulink model files. Use when the user asks to create a Simulink activity, Simulink Exercise, starter model, solution model, model-based learning activity, or Course Designer-ready Simulink artifact. Uses MATLAB MCP Server tool calls and Simulink Agentic Toolkit guidance to create, inspect, edit, simulate, and validate model files. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"
Create MATLAB Course Designer-ready Simulink Exercise learning activities. The skill must produce actual starter and solution model files, not only instructions. Use MATLAB MCP Server tool calls, following Simulink Agentic Toolkit guidance, to create, edit, inspect, and validate the models. The resulting activity folder should be ready for Course Designer web application import workflows, with `course-designer-activity.json` as the import-oriented metadata sidecar.
The user may have provided a module objective or activity idea in their request. If it is missing or too vague, collect the missing activity inputs in Step 1.
Read these references from the `references/` directory as needed:
Read `references/model-generation-workflow.md` and `references/course-designer-artifacts.md` before creating model files.
Use Simulink Agentic Toolkit guidance for model construction and inspection. When editing models, follow the `building-simulink-models` workflow:
1. Use `model_read` or `model_overview` before edits when a model exists. 2. Use `model_edit` for structural edits and parameter configuration. Treat a `status: partial` result as a failure until every reported parameter rejection is resolved and the intended values are confirmed with `model_query_params`; a partial edit can leave a block at a silently wrong default that `model_read` and `model_check` do not surface. 3. Use `model_read`, `model_overview`, and `model_query_params` to verify. 4. Use MATLAB MCP calls such as `evaluate_matlab_code`, `run_matlab_file`, `check_matlab_code`, and `detect_matlab_toolboxes` for model setup scripts, toolbox checks, simulation smoke tests, and file existence checks. 5. Use `model_test` for behavioral tests when a Gherkin validation spec is created, the testing workflow is available, and the model exposes at least one Inport; otherwise use the `matlab.unittest` fallback in `references/validation-rules.md`.
The `building-simulink-models` workflow starts with custom-library gates. For course activities built from base MATLAB and Simulink blocks, answer the custom-library question with "none" and keep the resulting `.satk/` configuration in the course output folder, not in this skill package.
Do not rely on prose-only model descriptions for final artifacts.
Step 1: Collect activity inputs and Course Designer placement Step 2: Confirm products, toolboxes, and output folder Step 3: Create the solution model with MCP tool calls Step 4: Create the starter model from the solution model Step 5: Validate solution and starter models Step 6: Write Course Designer-ready activity metadata and review notes
Collect only missing information:
verification, code generation, or another domain
model structure, or manual rubric
Default to a Course Designer learning activity type of `Simulink Exercise`.
Use `detect_matlab_toolboxes` when available to confirm MATLAB, Simulink, and required toolbox access. If a needed toolbox is missing, stop before creating a misleading model and report the blocked requirement.
Create or use this output folder:
simulink-activities/module-NN-activity-MM-[slug]/
All generated file names must be stable, lowercase, and Course Designer import friendly.
Use `references/model-generation-workflow.md`.
Create the complete solution model first. The solution model is the instructor reference and the source used to derive the starter model.
Required actions:
1. Create or open the model using MATLAB MCP calls. 2. Use `model_edit` for blocks, connections, parameters, model configuration, and subsystem structure. 3. Use `model_read` or `model_overview` to verify topology. 4. Save the model as:
[activity-slug]_solution.slx
Create the starter model from the validated solution model. Remove, mask, disable, parameterize, or replace only the parts learners are expected to complete.
Required actions:
1. Copy or save the solution model as:
[activity-slug]_starter.slx
2. Use `model_edit` to create the intended learner gaps. 3. Use `model_read` or `model_overview` to confirm the starter model still opens and contains the expected scaffold. 4. Do not leave broken model references, missing files, or unresolved variables unless they are explicitly part of the learner task.
Use `refe
A sandbox for prototyping and demonstrating Agent Skills for MATLAB and Simulink work. Skills here are experimental. They may be incomplete, change without notice, or migrate to an official toolkit over time.
Repo: matlab/agent-skills-playground
Use when a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any programming task where academic…
Use when tutoring a learner through MATLAB debugging, error interpretation, failed tests, incorrect outputs, array-shape problems, indexing mistakes, function…
Use when an AI tutor session concerns MATLAB programming concepts, MATLAB syntax, MATLAB errors, MATLAB code style, MATLAB projects, or MATLAB toolbox…
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…
Use when prompting a learner to complete hands-on MATLAB coding exercises, guided practice, debugging drills, code tracing, small MATLAB projects, or…
Use when creating, asking, grading, or explaining multiple choice questions for MATLAB programming practice, concept checks, quizzes, or tutoring exercises.