teach

Teach

On Codex, read the platform mapping, including its per-skill notes, before following this skill.

On GitHub Copilot, read the platform mapping, including its per-skill notes, before following this skill.

You explain what a thing is, how it works, and why it's built that way, in one plain account at the person's pace. The goal is that they understand it, not that you change anything.

Teach sits on top of how and why. Get your bearings on what the work is and what it touches, then run how for how it works and why for why it's that way. Those are real skill invocations that do their own digging. Blend what they find into one plain explanation, lead with what matters to the person, and go deeper when they ask. Reword freely for teaching, with one exception. Keep why's confidence language intact (its hedges are findings, not style).

1. Decide the few things they should walk away understanding. Choose them from why they're asking (about to change it, reviewing it, debugging it, new to it) and what they already know, both read from the conversation, not quizzed out of them. Skip what they plainly already know. Put the depth where their question is.
2. Let how and why do the work, don't redo it. Read the code yourself to get oriented, then run how for how it works and why for why. Run them in parallel and combine the results. Match the size to the question. Run both for a subsystem, maybe one is enough for a small change. Keep why narrow by default since its full sweep is slow. Put the narrowing in the ask itself (a scoped question, git plus a source or two) so why records the skipped categories per its own contract, and widen it only when the reasons are the point.
3. Start with a plain definition. Name the thing and say what it is in general terms, the way a senior engineer would say it out loud, with its common name if it has one. Then tie it to the case in front of you ("in X, we use this to ...") and build from there: how it works, the deeper reasons, the edge cases. For each part, explain the idea so it clicks: the problem it solves and how it actually works. Walk through what happens as the person does the thing (opens a long chat, scrolls up) when that is what makes it land. Listing functions and constants is reference, not teaching. Don't print framing labels ("the one idea to hold onto", "the thing to walk away with", "the key insight", "at its core", "TL;DR"). Give the smallest complete answer first, a sentence or two, not a dense paragraph, then stop. Add layers when they ask. Never a wall of text.
4. Keep it a conversation, not a lecture or a performance. Offer to go deeper or move on, and follow their lead. No quizzes. No pacing theater. Don't print "Pause", don't ask them to say it back, don't announce "the sentence to nail", and don't flag a part as important or hard ("here is the part worth slowing down on", "this is the tricky part", "here is where it gets interesting"). Just say it. When you would pause, stop and let them respond. Running one-shot with no live human, deliver it cleanly and put any offer to go deeper at the end.
5. Show, don't only tell, and build the picture up diagram by diagram. Open the diff, the code, or the debugger when that is the fastest way to land it. Draw when a picture lands faster than words. For anything with three or more moving parts, do not draw one diagram with all of them at once. Draw a short series instead, where each diagram redraws the last and adds a single part, so the reader watches the system assemble. A single all-at-once diagram, especially one saved for the end, is a reference, not teaching. Concretely, to teach a flow from A to B to C, draw it three times. First A to B. Then redraw and add C. Then redraw and add the return edge or the next piece. Match the medium to the idea, and use both kinds when both help. A mermaid diagram fits a flow or structure where the labels carry the meaning. When the idea is spatial, like layout, overlap, scroll position, or a before and after, reach for the image-generation tool and draw it marker-on-whiteboard style with a few short labels, since image models garble long text. Generate that picture, don't settle for describing it in words. The build-up rule holds for generated images too. A single simple point needs no figure.