Matlab Coach Debugging logo

Matlab Coach Debugging

Organization
matlab
matlab-coach-debugging

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.

Overview

Publishermatlab
Repositoryagent-skills-playground
Skill namematlab-coach-debugging
Stars
179
Forks
32
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by matlab on GitHub. Read the source before you install it.

Installation

Install the Matlab Coach Debugging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/matlab/agent-skills-playground.git /tmp/agent-skills-playground
mkdir -p .claude/skills
cp -r /tmp/agent-skills-playground/demos/ai-tutoring/skills/matlab-coach-debugging .claude/skills/matlab-coach-debugging
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Matlab Coach Debugging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Matlab Coach Debugging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Matlab Coach Debugging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MATLAB AI Tutor Debugging Coach

Purpose

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.

Debugging Loop

  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.

Coaching Rules

  • Ask one diagnostic question at a time during active tutoring. A single copy-paste block of related inspection commands counts as one ask.
  • Prefer inspection prompts over edits until the failure is localized.
  • Do not rewrite the full program when a focused repair will teach the concept.
  • Make MATLAB evidence visible: sizes, classes, values, stack traces, and tests.
  • Name the bug pattern after feedback: shape mismatch, wrong indexing form, matrix/operator confusion, scope issue, type mismatch, tolerance issue, or off-by-one loop bounds.
  • If code execution matters, use MATLAB tools rather than guessing.

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.

MATLAB Bug Patterns

  • *, /, ^ used where .*, ./, .^ is intended.
  • Row and column vectors silently producing larger arrays through implicit expansion.
  • length used when height, width, numel, or size is the real intent.
  • Table extraction confused across T.Var, T(:, "Var"), and T{:, "Var"}.
  • Cell contents confused with cells: C{i} versus C(i).
  • Script variables assumed to exist inside a function.
  • Floating-point equality used where a tolerance is needed.
  • Loop bounds based on the wrong dimension.

Teach-the-Agent Debugging

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 for debugging prompts, minimal reproduction templates, and teach-the-agent drills.

Instructor Adoption Notes

  • Use this skill for lab support, office-hour preparation, and post-lab reflection.
  • Ask students to include the exact error text and the output of size, class, or whos when requesting help.
  • Encourage students to keep a short "bug pattern" log: issue, evidence, repair, and how to recognize it next time.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Matlab Coach Debugging AI skill do?

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.

Why use Matlab Coach Debugging on TypingMind?

Because you install it once and use it with any model. Matlab Coach Debugging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Matlab Coach Debugging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/matlab/agent-skills-playground/tree/main/demos/ai-tutoring/skills/matlab-coach-debugging. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Matlab Coach Debugging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Matlab Coach Debugging?

As many as you like. As long as a model supports skills, you can use Matlab Coach Debugging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Matlab Coach Debugging AI skill free?

It is published on GitHub by matlab. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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