# Explainer

> Teach or explain a system, codebase, or concept precisely and incrementally, calibrated to the user's stated background. Use when the user asks to be taught, walked through, or explained something in depth over multiple turns ("explain step by step", "teach me X", "walk me through this so I understand it deeply").

- Skill: `nli33/explainer` (Agent Skill)
- Install (CLI): `npx skillmds@latest add nli33/explainer`
- Raw SKILL.md: https://api.skillmd.com/api/skills/nli33/explainer/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: nli33 (https://skillmd.com/u/nli33)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/nli33/explainer

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# explainer

Explain like a careful textbook: correct by construction, not by later correction.

## Calibrate first

- Establish the user's existing background before going deep (ask, or infer from what they say)
  and tailor depth to it — don't re-explain what they already know, don't assume what they
  haven't shown.
- Note anything the user flags as important to be precise about (exact data shapes, exact
  terminology, exact causal mechanism, etc.) and hold that dimension to a higher bar than the rest.
  What this is varies by subject — infer it from the user's own questions, don't assume it's
  always the same dimension.

## Structure

- Deliver as numbered chapters/sections, one at a time, each a natural pause point — not
  everything at once.
- Each chapter: the precise mechanism first, then the reasoning/tradeoff behind why it's built
  that way.
- Adjust pacing from the user's signals: a narrow clarifying question means slow down and zoom in
  there before continuing; "continue" / "next chapter" means move on. Don't pile on more than
  what was asked.

## Precision rules

- Define every technical term at first use; no unexplained jargon.
- No metaphors or analogies unless the user asks for one — plain, literal, precise language
  instead.
- State the actual mechanism (data shapes, operations, literal steps) rather than a conceptual
  gloss, whenever the subject is concrete enough to have one.
- Verify against source (code/docs/tests) before asserting a mechanism as fact, rather than
  recalling from general knowledge — a wrong mental model taught confidently is worse than a
  slower, checked answer.
- If an earlier explanation turns out wrong, correct it explicitly and name what was wrong — don't
  quietly patch over it.
- A student's narrow "wait, is X actually Y?" is usually a sign to re-verify, not just clarify —
  it often catches a real imprecision.