# Teach Me > Teach me my unknowns — an interactive explainer for a domain's vocabulary and mental model, so vague requests become precise. Use on "teach me", "make me an explainer", or when the user cannot name what they want. Blindspot investigates a codebase; teach-me teaches vocabulary. - Skill: `ajitta/teach-me` (Agent Skill) - Install (CLI): `npx skillmds@latest add ajitta/teach-me` - Raw SKILL.md: https://api.skillmd.com/api/skills/ajitta/teach-me/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: ajitta (https://skillmd.com/u/ajitta) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/ajitta/teach-me --- # Teach Me — Domain Vocabulary Explainer (Teach Me My Unknowns) Vague requests ("make it better") usually stem from **missing vocabulary**, not missing taste. This skill fills the **concept/terminology gap** among unknown unknowns. Origin: Teach Me My Unknowns — see skills/loop/references/talk-source.md ## Iron Rules 1. **Do not start the work yet.** Teach first, so the user can make the request precise. 2. Teach **only vocabulary needed for decisions**, not an encyclopedia — start from the axes the user must choose on in this task. ## Procedure 1. Parse domain, goal, current level from `$ARGUMENTS`. Empty → the domain of the work under discussion; if still unclear, ask once, briefly. 2. Open with the **mental model**: the domain's pipeline in 3–5 ordered stages (color grading: ingest → correct → grade → match), so the user knows what comes before what — correction first, then the creative look. 3. Pick 3–7 **decision axes** the user will decide on in this task (e.g. color grading: exposure / white balance / contrast curve / saturation vs naturalness / look). 4. Build a **vocabulary ladder**: per axis, everyday word → expert term, each term with 1 example sentence of "what you can request with this term". 5. Show a **before/after comparison** per concept — same subject with vs without the concept applied. Visual domains: synthetic inline comparisons (SVG/canvas, or CSS filters over two rendered states), never external image URLs; if a real photo is essential, ask the user for a file and embed it as a `data:` URI. Code/writing: comparison examples. Add 2–3 named presets (e.g. flat / corporate clean / cinematic teal-orange) so a whole look can be felt at once, not only single sliders. 6. Give **what good looks like**: 4–6 judging criteria stated in the new vocabulary (e.g. "skin tones stay believable", "blacks are rich but not crushed"). 7. Close with the payoff — a **precise-request draft rewriting the user's original request in the new vocabulary**. User picks items and adjusts values/direction; the result becomes the next prompt. Offer with one AskUserQuestion: use this request now / edit it first / stop here. ## Output Artifact tool → publish the page; else `.unknowns/-teach-me-.html`; else markdown. Reaction control: an "include in my request" checkbox per concept (plus live before/after sliders and presets); checked items assemble into the precise-request draft. Details: skills/loop/references/output-routing.md ## Limits — what this can and cannot deliver Vocabulary hands over a **request**, not fluency. Domain fluency is collective tacit knowledge, acquired by immersion in a discourse community, and does not transfer as a term list (Collins, *Tacit and Explicit Knowledge*, 2010). So: - **Expect**: the user's *next* request to be markedly more precise. - **Do not expect**: the vocabulary to be wielded unaided across revision rounds 2–4 — the predicted failure point, where terms must be *used* rather than pasted. - When revisions stop converging, that is this skill's ceiling, not the user's mistake. Hand off to `/unknowns:interview` (or `/interview`) to lock decisions rather than teaching more vocabulary. **Success signal is convergence across revision rounds 2–4, not the quality of the first rewritten request.** Step 6 is what buys those later rounds: judging criteria transfer far better than production vocabulary, because recognising a bad result is a cheaper skill than knowing which axis to move. Keep step 6 even when trimming for size. ## Related - Codebase blind spots: run `/unknowns:blindspot` (or `/blindspot` for copied installs) first — teach-me covers blind spots in domain **concepts**. Running both is fine. - If requirements still diverge after gaining vocabulary, lock decisions with `/unknowns:interview`.