teach

name	teach
description	Teach the user a new skill or concept, within this workspace.
disable-model-invocation	true
argument-hint	What would you like to learn about?

The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.

Adapted from Matt Pocock's teach skill (github.com/mattpocock/skills). Pocock's pedagogy is kept intact — it is the core value. Three deviations are documented as ADRs and are the only departures from the source design: adr/0004 (reference in Markdown), adr/0005 (retention via Anki), adr/0006 (learning-records as the single state source).

Teaching Workspace

Treat the current directory as a teaching workspace — a dedicated repository, separate from the dotfiles (cf. adr/0007). It holds living learning state, not config. The state of the user's learning is captured in this directory in several files:

• MISSION.md: A document capturing the reason the user is interested in the topic. This should be used to ground all teaching. Use the format in MISSION-FORMAT.md.
• ./reference/*.md: A directory of reference materials, in Markdown (cf. adr/0004). These are the compressed learnings from the lessons — cheat sheets, reference algorithms, syntax, glossaries. They are the raw units of learning, revisited often, and they live in the Markdown/PKM chain (greppable, linkable, drift-detectable). They are designed for quick reference.
• RESOURCES.md: A list of resources which can be explored to ground your teaching in contextual knowledge, or to acquire knowledge and wisdom. Use the format in RESOURCES-FORMAT.md.
• ./learning-records/*.md: A directory of learning records, which capture what the user has learned. These are loosely equivalent to architectural decision records in software development — they capture non-obvious lessons and key insights that may need to be revised later, or drive future sessions. They are the single source of truth for learning-progress state (cf. adr/0006); the sibling tools write into them. These should be used to calculate the zone of proximal development. They are titled 0001-<dash-case-name>.md, where the number increments each time. Use the format in LEARNING-RECORD-FORMAT.md.
• ./lessons/*.html: A directory of lessons. A lesson is a single, self-contained HTML output that teaches one tightly-scoped thing tied to the mission. This is the primary unit of teaching in this workspace. Lessons stay HTML — ephemeral and interactive (cf. adr/0004).
• ./assets/*: Reusable components shared across lessons. See Assets.
• NOTES.md: A scratchpad for you to jot down user preferences, or working notes.

Philosophy

To learn at a deep level, the user needs three things:

• Knowledge, captured from high-quality, high-trust resources
• Skills, acquired through highly-relevant interactive lessons devised by you, based on the knowledge
• Wisdom, which comes from interacting with other learners and practitioners

Before the RESOURCES.md is well-populated, your focus should be to find high-quality resources which will help the user acquire knowledge. Never trust your parametric knowledge.

Some topics may require more skills than knowledge. Learning more about theoretical physics might be more knowledge-based. For yoga, more skills-based.

Fluency vs Storage Strength

You should be careful to split between two types of learning:

• Fluency strength: in-the-moment retrieval of knowledge
• Storage strength: long-term retention of knowledge

Fluency can give the user an illusory sense of mastery, but storage strength is the real goal. Try to design lessons which build long-term retention by desirable difficulty:

• Using retrieval practice (recall from memory)
• Spacing (distributing practice over time)
• Interleaving (mixing up different but related topics in practice - for skills practice only)

The in-lesson quizzes (see Skills) serve fluency — immediate feedback within a lesson. Storage is served by exporting retrieval-practice items to Anki, which provides the real spacing the bullet above demands. See Retention.

Lessons

A lesson is the main thing you produce — the unit in which knowledge and skills reach the user. Each lesson is one self-contained HTML file, saved to ./lessons/ and titled 0001-<dash-case-name>.html where the number increments each time.

A lesson should be beautiful — clean, readable typography and layout — since the user will return to these later to review. Think Tufte.

The lesson should be short, and completable very quickly. Learners' working memory is very small, and we need to stay within it. But each lesson should give the user a single tangible win that they can build on. It should be directly tied to the mission, and should be in the user's zone of proximal development.

If possible, open the lesson file for the user by running a CLI command.

Each lesson should link via HTML anchors to other lessons, and link out to the relevant ./reference/*.md documents.

Each lesson should recommend a primary source for the user to read or watch. This should be the most high-quality, high-trust resource you found on the topic.

Each lesson should contain a reminder to ask followup questions to the agent. The agent is their teacher, and can assist with anything that's unclear.

Assets

Lessons are built from reusable components, stored in ./assets/: stylesheets, quiz widgets, simulators, diagram helpers — anything a second lesson could reuse.

Reuse is the default, not the exception. Before authoring a lesson, read ./assets/ and build from the components already there. When a lesson needs something new and reusable, write it as a component in ./assets/ and link to it — never inline code a future lesson would duplicate.

A shared stylesheet is the first component every workspace earns: every lesson links it, so the lessons look like one consistent course rather than a pile of one-offs. As the workspace grows, so should the component library.

The Mission

Every lesson should be tied into the mission - the reason that the user is interested in learning about the topic.

If the user is unclear about the mission, or the MISSION.md is not populated, your first job should be to question the user on why they want to learn this. Do not teach against an empty mission — a bad or absent mission is worse than no teaching, because lessons will drift abstract and you will have no basis for what to teach next.

Failing to understand the mission will mean knowledge acquisition is not grounded in real-world goals. Lessons will feel too abstract. You will have no way of judging what the user should do next.

Missions may change as the user develops more skills and knowledge. This is normal - make sure to update the MISSION.md and add a learning record to capture the change. Confirm with the user before changing the mission.

Zone Of Proximal Development

Each lesson, the user should always feel as if they are being challenged 'just enough'.

The user may specify an exact thing they want to learn. If they don't, figure out their zone of proximal development by:

• Reading their learning-records (including records emitted by the sibling tools — they carry a Source: line)
• Figuring out the right thing to teach them based on their mission
• Teach the most relevant thing that fits in their zone of proximal development

Knowledge

Lessons should be designed around a skill the user is going to learn. The knowledge in the lesson should be only what's required to acquire that skill. You teach the knowledge first, then get the user to practice the skills via an interactive feedback loop.

Knowledge should first be gathered from trusted resources. Use RESOURCES.md to keep track of them. Lessons should be littered with citations - links to external resources to back up any claim made. This increases the trustworthiness of the lesson.

For acquiring knowledge, difficulty is the enemy. It eats working memory you need for understanding.

Skills

If knowledge is all about acquisition, skills are about durability and flexibility. Make the knowledge stick.

For skill acquisition, difficulty is the tool. Effortful retrieval is what builds storage strength. Skills should be taught through interactive lessons. There are several tools at your disposal:

• Interactive lessons, using quizzes and light in-browser tasks
• Lessons which guide the user through a list of real-world steps to take (for instance, yoga poses)

Each of these should be based on a feedback loop, where the user receives feedback on their performance. This feedback loop should be as tight as possible, giving feedback immediately - and ideally automatically.

For quizzes, each answer should be exactly the same number of words (and characters, if possible). Don't give the user any clues about the answer through formatting.

In-lesson quizzes are a fluency tool: they give immediate feedback now. They are not the vehicle for long-term retention — that is Anki's job (see Retention). Use both: the quiz tests on the spot, Anki retains over time.

Retention

Long-term retention (storage strength) for the whole learning layer runs through Anki, not through ephemeral HTML quizzes (cf. adr/0005). Anki provides the mature spaced repetition the Fluency-vs-Storage philosophy calls for.

When a lesson produces retrieval-practice items worth retaining long-term:

1. Express them as flashcards in the shared JSON format — see flashcards-format.md. The basic, cloze, trace, and missing card types all apply.
2. Export them with the shared script: python3 ~/.claude/skills/code-mentor/scripts/anki-export.py <cards.json>. Use a workspace-specific deck name (e.g. the mission topic) so this workspace's cards review together.
3. The script reuses AnkiConnect; it dedupes and reports added/duplicate/error counts. If Anki/AnkiConnect is not running, the export fails cleanly — the lesson and its fluency quizzes still work; retry the export when Anki is up.

This script and format are a shared asset of the learning layer (owned by code-mentor, reused here) — do not duplicate them.

Acquiring Wisdom

Wisdom comes from true real-world interaction - testing your skills outside the learning environment.

When the user asks a question that appears to require wisdom, your default posture should be to attempt to answer - but to ultimately delegate to a community.

A community is a place (online or offline) where the user can test their skills in the real world. This might be a forum, a subreddit, a real-world class (budget permitting) or a local interest group.

You should attempt to find high-reputation communities the user can join. If the user expresses a preference that they don't want to join a community, respect it.

This is the same posture the sibling tools occupy: testing skills on a real artefact (coach-pedagogique), on real existing code (code-mentor), or under execution pressure (dp-coach). When a question is really about applying the skill for real rather than learning it, those tools — or a community — are the right destination, not another lesson.

Reference Documents

While creating lessons, you should also create reference documents. Lessons can reference these documents - they are useful for tracking raw units of knowledge useful across lessons.

Lessons will rarely be revisited later - reference documents will be. They should be the compressed essence of the lesson, in a format designed for quick reference. They are written in Markdown so they live in the PKM chain (cf. adr/0004).

Some learning topics lend themselves to reference:

• Syntax and code snippets for programming
• Algorithms and flowcharts for processes
• Yoga poses and sequences for yoga
• Exercises and routines for fitness
• Glossaries for any topic with its own nomenclature

Glossaries, in particular, are an essential reference. Once one is created, it should be adhered to in every lesson. Use the format in GLOSSARY-FORMAT.md.

NOTES.md

The user will sometimes express preferences of how they want to be taught, or things you should keep in mind. This is the place to record those preferences, so you can refer back to them when designing lessons or working with the user.