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flashcards

Use when creating, testing, or updating active-recall flashcards grounded in session concepts to reinforce retention.

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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

Installationsoptionen

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
flashcards
description
Use when creating, testing, or updating active-recall flashcards grounded in session concepts to reinforce retention.
version
1.1.0
authors
["edu-agent-skills contributors"]
tags
["productivity","flashcards","active-recall","retention"]
status
stable
# Purpose Convert session concepts into structured active-recall flashcards. Cards must test reasoning and application, not simple definitions, to build durable understanding. # Activation - Concept teaching session just completed. Learner requests cards. `spaced-repetition` needs card generation/update. Revision period (exam, interview, milestone). - **Skip if**: concept hasn't been taught yet. Goal is deep exploration → `deep-dive`. Active debugging/project work → would interrupt flow. - **Routing**: generate cards *after* understanding is confirmed. Feed into `spaced-repetition` for scheduling. Cards failed 3 times → trigger `misconception-detector`. # Inputs - Concepts/skills covered, learner's confirmed level, existing card set (if updating), error patterns from assessment skills. # Card Types - **Concept**: "What is X?" → vocabulary accuracy. - **Mechanism**: "Trace what happens when X executes." → process understanding. - **Tradeoff**: "When would you NOT use X?" → decision reasoning. - **Application**: "Given [context], which [tool/pattern] and why?" → transfer. - **Debug**: "What's wrong with this code?" → diagnostic thinking. Prefer Mechanism, Tradeoff, and Application types (higher transfer value). At least 60% of cards should be these types. # Workflow 1. **Extract** — Identify 3–7 key concepts worth card-ifying. Prioritize mechanisms, tradeoffs, application patterns. Skip long-mastered concepts. 2. **Generate** — 1–2 cards per concept. Front = question (not keyword). Back = complete model response (~100 words max). Verify: front is unambiguous, back is concise but complete, card tests reasoning not verbatim recall. 3. **Test** — Present front only; learner responds before seeing back. Self-score: Easy (fluent) / Hard (needed effort) / Failed (wrong/blank). Update interval. 4. **Handle Failures** — Failed card: re-test after 10 minutes in same session. Same card failed 3 times across sessions: suspend and trigger `misconception-detector`. 5. **Update** — After any misconception correction: update affected card backs. Never leave outdated cards in the deck. # Rules - DO: card fronts must be questions, not keywords. - DO: backs must require explanation, not one-word answers. - DO: test at least 3 cards in active-recall mode during generation session. - DO: cross-reference cards for connected concepts. - DON'T: generate all "What is X?" cards — that's definition-only bias. - DON'T: let decks grow unbounded — flag cards with ease_factor > 2.5 for 5+ sessions as mastered. - DON'T: generate cards before understanding is confirmed. - DON'T: skip active testing — generation is not the end state. # Output Card generation: topic, date, cards (front + back + type + difficulty). Active recall: front shown, learner responds, back revealed, score + next review date. Format naturally. # Checklist - [ ] 60%+ cards are Mechanism/Tradeoff/Application type. - [ ] Each card front is a clear question; back is a complete response. - [ ] At least 3 cards tested in active-recall this session. - [ ] Cards updated after any misconception correction.
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