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Codebase To Course

Community
JasonxzWen
codebase-to-course

Load when a user wants a source-backed interactive HTML course that explains how a codebase works; do not load for chat tutoring, repository review, articles, slide decks, or general browser artifacts.

Overview

PublisherJasonxzWen
Repositoryharness-hub
Skill namecodebase-to-course
Stars
71
Forks
0
Bundled files
Instructions only
LicenseMIT
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Codebase To Course 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/JasonxzWen/harness-hub.git /tmp/harness-hub
mkdir -p .claude/skills
cp -r /tmp/harness-hub/skills/codebase-to-course .claude/skills/codebase-to-course
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codebase To Course 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 Codebase To Course 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 Codebase To Course 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.

Codebase to Course

Turn a real codebase into a factual, interactive HTML course for a reader who needs to understand and change the system, not memorize terminology.

Routing

This Skill owns a course artifact whose subject is a codebase.

  • Use quick-learn for multi-session teaching, assessment, and durable learner progress.
  • Use code-review for findings about correctness or maintainability.
  • Use source-post for a public article.
  • Use frontend-slides for a presentation.
  • Use web-artifacts-builder only when accepted course interactions genuinely need an application framework rather than a self-contained document.

Do not combine those outputs by default. A course is a learning artifact, not a review report with quizzes attached.

Evidence Contract

Inspect before explaining:

  1. Read the repository contract, README, entry points, configuration, tests, and the smallest set of implementation files needed to trace one representative user or operator journey.
  2. Identify the system's real actors, ownership boundaries, data movement, external dependencies, and one meaningful failure or debugging path.
  3. Separate observed facts from inference. Every implementation claim in the course must point to a current repository-relative file and line or symbol anchor.
  4. Use only short, exact source snippets. Do not simplify source code and present the result as verbatim code.
  5. Exclude credentials, secrets, customer data, generated vendor trees, and unrelated proprietary material. A course never expands access authority.

If the subject is a public repository URL, use read-only access or a temporary checkout. Do not modify or publish back to the source repository.

Course Shape

Choose the fewest modules that form a coherent teaching arc. Cover only what the source proves and the learner needs:

  • what the product or tool does and the concrete journey being traced;
  • the main actors and why each owns its responsibility;
  • how control and data cross boundaries;
  • one or more exact code-to-plain-language explanations;
  • a failure path that builds practical debugging intuition;
  • scenario questions that ask the learner to apply the model to a change or incident.

Define unfamiliar terms at first use. Prefer a diagram, annotated flow, or compact comparison when it teaches the relationship more clearly than prose. Avoid decorating every section with the same card pattern.

Scenario questions must test transfer, such as which boundary should change or where a symptom likely originates. Do not quiz acronym expansion, syntax trivia, or filename recall.

Artifact Contract

Default to one self-contained codebase-course.html with inline CSS and JavaScript. Use adjacent assets only when the course needs user-supplied images that cannot reasonably be embedded.

The artifact must provide:

  • a clear reading order and module navigation;
  • visible progress without locking the reader into mandatory scroll snapping;
  • at least one source-backed architecture or data-flow visual;
  • short exact code excerpts paired with plain-language interpretation and source anchors;
  • at least one interactive scenario check with accessible controls and non-punitive feedback;
  • keyboard access, visible focus, responsive layout, sufficient contrast, and reduced-motion behavior;
  • a source index that lets a maintainer reopen every cited file.

Keep interactions native and small. Add a framework, build pipeline, persistence layer, or external font only when the accepted course behavior requires it.

Verification

Before handoff:

  1. Re-read every cited source anchor and correct stale line references or claims.
  2. Confirm no source excerpt contains secrets or unrelated personal/project data.
  3. Open the final HTML and exercise navigation plus every scenario control.
  4. Check the console and inspect the densest module at desktop and narrow mobile widths.
  5. Verify the artifact works without a network connection when it is described as self-contained.

Report any inference, inaccessible source, unverified browser behavior, or intentionally omitted subsystem. A visually polished course with stale code facts is a failed artifact.

Frequently asked questions

What does the Codebase To Course AI skill do?

Load when a user wants a source-backed interactive HTML course that explains how a codebase works; do not load for chat tutoring, repository review, articles, slide decks, or general browser artifacts.

Why use Codebase To Course on TypingMind?

Because you install it once and use it with any model. Codebase To Course 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 Codebase To Course in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JasonxzWen/harness-hub/tree/main/skills/codebase-to-course. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Codebase To Course?

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 Codebase To Course?

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

Is the Codebase To Course AI skill free?

Yes. It is published on GitHub by JasonxzWen under the MIT license. 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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