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deep-dive

Use when a learner has surface understanding and needs to explore mechanism, tradeoffs, edge cases, and production implications at depth.

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Quellinformationen

Repository
yugash007/edu-agent-skills
Letzte Quellaktivität
18. Mai 2026 um 16:48
Erkannte Sprache von SKILL.md
Englisch
Sterne
7
Forks
2

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Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
deep-dive
description
Use when a learner has surface understanding and needs to explore mechanism, tradeoffs, edge cases, and production implications at depth.
version
1.1.0
authors
["edu-agent-skills contributors"]
tags
["teaching","depth","mechanism","advanced-learning"]
status
stable
# Purpose Take a learner from surface understanding to genuine depth on a single concept. Assumes the learner has a working mental model and pushes into mechanism, failure modes, tradeoffs, and production implications. Exit condition: learner can reason about the concept in novel, constrained contexts. # Activation - Learner asks to go deeper on a known concept. `check-understanding` confirms surface competence but weak mechanism knowledge. Interview prep or architectural decision needs depth. - **Skip if**: beginner encountering concept for the first time → `teach-concept`. Needs immediate practical help → `build-with-me`/`debug-teacher`. Has a misconception → `misconception-detector` first. - **Routing**: confirm current level with a quick probe before starting. Pair with `challenge-generator` at the end for advanced application. # Inputs - Target concept, confirmed current understanding level, motivating context (interview/architecture/debugging), known gaps or questions. # Depth Ladder Five rungs, each confirmed before ascending: 1. **Surface** — Definition and intuition → "State this in one sentence." 2. **Mechanism** — Step-by-step how it works → "Trace a concrete execution." 3. **Tradeoffs** — When it works vs. doesn't → "What would you choose instead, and why?" 4. **Edge Cases** — Boundaries and failures → "What breaks this?" 5. **Production** — Real-world tuning, monitoring, debugging → "How would you debug this at 3am?" # Workflow 1. **Entry Check** — Ask one question to confirm starting rung. Skip confirmed rungs; jump to the frontier. 2. **Mechanism (Rung 2)** — Walk through with a concrete worked trace. Require learner to narrate it back. 3. **Tradeoffs (Rung 3)** — Present a decision context. Elicit learner's reasoning before canonical analysis. Include one case where the naive choice is wrong. 4. **Edge Cases (Rung 4)** — Pose 2–3 edge case questions. Require learner to surface them first, then supplement. For each: symptom + fix. 5. **Production (Rung 5)** — Observability, performance under load, tuning knobs, known failure patterns. Ground in a realistic system. Ask: "If this broke at 3am, what's your investigation sequence?" 6. **Exit Synthesis** — Ask learner to produce a one-paragraph explanation for someone who just learned the basics. # Rules - DO: confirm each rung before ascending — require exit question answers. - DO: require learner narration at Rung 2, learner tradeoff reasoning at Rung 3, learner-surfaced edge cases at Rung 4. - DO: use realistic scale at Rung 5 — not toy numbers. - DON'T: re-teach confirmed surface level — skip to the frontier. - DON'T: lecture all five rungs without learner participation at every rung. - DON'T: end without learner producing an exit synthesis paragraph. # Output Responses should contain: context (concept + starting rung + motivation), depth ladder progress, current rung exploration, checkpoint question, and exit synthesis prompt. Format naturally per rung. # Checklist - [ ] Entry level confirmed; confirmed rungs skipped. - [ ] Learner participation required at every rung. - [ ] Rung 5 reached for intermediate+ learners. - [ ] Exit synthesis produced by learner.
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