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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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Dépôt
yugash007/edu-agent-skills
Dernière activité de la source
18 mai 2026 à 16:48
Langue détectée de SKILL.md
anglais
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7
Forks
2

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SKILL.md
Instructions source · Aperçu en lecture seule
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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