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Teach

Matt PocockCommunityCreated by Matt Pocock

  • Skill
  • Role or persona
  • Education and learning
  • MIT
  • No issues found

From the author

Teach the user a new skill or concept, within this workspace.
— the description by Matt Pocock

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The teach skill provides a comprehensive environment for mastering new subjects. It operates as a stateful workspace where an agent acts as a tutor, grounding all instruction in a user-defined mission. By balancing knowledge acquisition with skill-based practice, the system promotes long-term retention through spaced repetition and effortful retrieval. It maintains a library of self-contained HTML lessons, reusable assets, and reference documents, ensuring that learning is both modular and cumulative. The process is designed to keep the user within their zone of proximal development, adapting to their progress over time.

What it does

  • Establishes a mission-driven learning workspace to ground all educational activities.
  • Generates modular, self-contained HTML lessons tailored to the user's current progress.
  • Creates and maintains reference documents like glossaries and cheat sheets for long-term utility.
  • Tracks learning history via structured records to adapt future content to the user's needs.
  • Curates high-trust external resources to support knowledge acquisition.
  • Encourages real-world application and community engagement to foster wisdom.

When to use it

  • When you want to learn a new skill or concept over multiple sessions.
  • When you need a structured approach to track your progress and retain complex information.
  • When you prefer learning through a mix of theory and interactive, hands-on practice.
  • When you need a personalized curriculum that adapts to your specific goals and pace.

Advantages

  • Promotes deep learning by distinguishing between fluency and long-term storage strength.
  • Ensures consistency and quality through reusable components and shared stylesheets.
  • Provides a persistent, organized workspace for reviewing past lessons and reference materials.
  • Adapts to the user's zone of proximal development for optimal challenge levels.
  • Encourages active recall and spaced practice to improve memory retention.

Usage examples

“I want to learn how to play chess.”
The agent establishes a chess-learning workspace, defines a mission, and creates the first lesson on basic piece movement.
“Teach me the basics of Python programming.”
The agent initializes a programming workspace, creates a mission document, and begins with a lesson on basic syntax.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/mattpocock/teach/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip teach.zip -d .agents/skills

Documentation by Matt Pocock

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

Teaching Workspace

Treat the current directory as a teaching workspace. Workspace paths (./lessons/ and the rest) resolve from the directory /teach was run in; only the *-FORMAT.md links resolve from this skill's folder. The state of their 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/*.html: A directory of reference materials. These are the compressed learnings from the lessons - cheat sheets, reference algorithms, syntax, yoga poses, glossaries. They are the raw units of learning. They should be beautiful documents which print out well, and 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. 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.

  • ./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)

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, with 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 reference 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, and anything else 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.

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

  • 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). Vary which position holds the correct answer across questions. Don't give the user any clues about the answer through formatting or order.

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.

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.

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.

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.

Files

GLOSSARY-FORMAT.md

GLOSSARY.md Format

GLOSSARY.md is the canonical language for this teaching workspace. All explainers, exercises, and learning records should adhere to its terminology. Building it is itself part of learning: compressing a concept into a tight definition is evidence the user understands it.

Structure

# {Topic} Glossary

{One or two sentence description of the topic this glossary covers.}

## Terms

**Hypertrophy**:
Muscle growth driven by mechanical tension and metabolic stress over repeated training sessions.
_Avoid_: Bulking, getting big

**Progressive overload**:
Systematically increasing the demand on a muscle over time, via load, volume, or intensity.
_Avoid_: Pushing harder, levelling up

**RPE (Rate of Perceived Exertion)**:
A 1–10 self-rating of how hard a set felt, where 10 is failure and 8 means two reps left in the tank.
_Avoid_: Effort score, intensity rating

Rules

  • Add a term only when the user understands it. The glossary is a record of compressed knowledge, not a dictionary the user reads to learn. If the user has just been introduced to a concept, wait until they can use it correctly before promoting it here.

  • Be opinionated. When several words exist for the same concept, pick the best one and list the rest as aliases to avoid. This is how language compresses.

  • Keep definitions tight. One or two sentences. Define what the term IS, not what it does or how to do it.

  • Use the glossary's own terms inside definitions. Once a term is in the glossary, prefer it everywhere, including inside other definitions. This is what makes complex terms easier to grasp later.

  • Group under subheadings when natural clusters emerge (e.g. ## Anatomy, ## Programming). A flat list is fine when terms cohere.

  • Flag ambiguities explicitly. If a term is used loosely in the wider field, note the resolution: "In this workspace, 'set' always means a working set; warm-ups are tracked separately."

  • Revise as understanding deepens. A definition the user wrote in week one may be wrong by week six. Update in place; do not leave stale entries.

Requirements and compatibility

Written for: Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

Security

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Attribution and licence

Created by
Matt Pocock
Publisher
Matt Pocock (Community)
Source
mattpocock/skills · skills/productivity/teach · commit 4ae2317
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download teach.zip