matlab-apply-assignmen…
Use when a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any…
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,
Claude Code
$ npx -y skills add matlab/agent-skills-playground --skill matlab-coach-debugging --agent claude-code
Codex
$ npx skills add matlab/agent-skills-playground --skill matlab-coach-debugging -a codex -y
Cursor
$ npx skills add matlab/agent-skills-playground --skill matlab-coach-debugging -a cursor -y
Gemini CLI
$ npx skills add matlab/agent-skills-playground --skill matlab-coach-debugging -a gemini-cli -y
GitHub Copilot
$ npx skills add matlab/agent-skills-playground --skill matlab-coach-debugging -a github-copilot -y
OpenCode
$ npx skills add matlab/agent-skills-playground --skill matlab-coach-debugging -a opencode -y
Windsurf
$ npx skills add matlab/agent-skills-playground --skill matlab-coach-debugging -a windsurf -y
name: matlab-coach-debugging description: 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. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"
Coach learners through MATLAB debugging as evidence gathering. Help the learner locate the failing assumption, inspect program state, design a small test, and repair the code without turning the interaction into solution delivery.
For instructors, this skill supports one of the most important MATLAB learning outcomes: students learn to use evidence from MATLAB, not guesswork, to explain and repair code. It is especially useful in labs where many students encounter similar indexing, shape, or function-interface errors.
Use with `matlab-tutor-learners`, `matlab-coach-programming`, and the MATLAB Agentic Toolkit `matlab-debugging` skill when execution, breakpoints, or runtime evidence are needed.
1. **State expectation**: Ask what the learner expected the code to do. 2. **Capture evidence**: Get the exact error text or observed wrong output. 3. **Localize**: Identify the file, line, expression, and variable involved. 4. **Inspect state**: Ask for or run `size`, `class`, `whos`, and representative values. 5. **Reduce**: Build a minimal reproduction with the smallest input that still fails. 6. **Hypothesize**: Ask the learner to explain the likely cause before fixing. 7. **Test repair**: Apply one change and verify with a normal case and edge case. 8. **Transfer**: Ask how the same bug pattern would appear in nearby code.
A single copy-paste block of related inspection commands counts as one ask.
matrix/operator confusion, scope issue, type mismatch, tolerance issue, or off-by-one loop bounds.
When a student asks "what is wrong with my code?", the tutor should avoid starting with a replacement solution. Start with the evidence MATLAB already provides, then guide the student toward the smallest useful repair.
expansion.
Use this pattern when the learner needs conceptual practice rather than help with their own file:
1. Present a short flawed MATLAB explanation or snippet. 2. Ask the learner to identify the false claim or failing line. 3. Ask for evidence that proves the issue. 4. Ask for the smallest correction. 5. Ask for one test that distinguishes the flawed and corrected versions.
Read [references/debugging-patterns.md](references/debugging-patterns.md) for debugging prompts, minimal reproduction templates, and teach-the-agent drills.
reflection.
`class`, or `whos` when requesting help.
repair, and how to recognize it next time.
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.
Use when a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any…
Use when an AI tutor session concerns MATLAB programming concepts, MATLAB syntax, MATLAB errors, MATLAB code style, MATLAB…
Use when an instructor wants to create, interview for, configure, install, update, or review a course AI-use policy for MATLAB AI…
Use when prompting a learner to complete hands-on MATLAB coding exercises, guided practice, debugging drills, code tracing, small…
Use when creating, asking, grading, or explaining multiple choice questions for MATLAB programming practice, concept checks,…
Use when reviewing, auditing, scoring, or improving a real or synthetic MATLAB AI tutor transcript, tutoring prompt, generated…
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.