| name | universal-flashcard-generator |
| description | Converts any study material (notes, textbooks, syllabus topics, PYQs) into optimized flashcards for ANY university worldwide. Supports 6 flashcard types across 3 difficulty tiers with built-in Spaced Repetition System (SRS) metadata. Exports to Anki, Quizlet, CSV, and text formats. Works for ALL subjects, ALL departments. |
Universal Flashcard Generator
Overview
Transforms any study material into exam-optimized flashcards. Uses cognitive science principles
(active recall, spaced repetition, elaboration, interleaving) to maximize retention. Generates
SRS-ready decks with proper scheduling metadata for long-term memory consolidation.
How This Skill Works
- User provides: Source material (notes, textbook chapters, syllabus topics, question papers,
or any text)
- System analyzes: Content structure, subject type, Bloom's level distribution, exam patterns
- System selects: Optimal flashcard types based on content characteristics and learning goals
- System generates: Formatted flashcard deck with SRS scheduling metadata
- System exports: In requested format (Anki APKG, Quizlet CSV, plain text, or markdown)
1. Flashcard Types
Type A — Basic Fact (Recall)
| Element | Description |
|---|
| Front | Direct question or prompt |
| Back | Concise answer (1-3 sentences) |
| Best for | Definitions, dates, formulas, terminology, lists |
| Bloom's Level | Remember |
| Example Front | What is the time complexity of binary search? |
| Example Back | O(log n) in the average and worst case |
Type B — Cloze Deletion
| Element | Description |
|---|
| Front | Sentence with key term blanked: The capital of France is {{c1::Paris}} |
| Back | Full sentence with revealed term |
| Best for | Fill-in-the-blank style recall, language learning, definitions |
| Bloom's Level | Remember, Understand |
| Example Front | The three pillars of {{c1::sustainable development}} are economic, social, and environmental. |
Type C — Concept Association
| Element | Description |
|---|
| Front | Concept, term, or scenario |
| Back | Related concept, application, or counter-example |
| Best for | Linking related ideas, compare/contrast, "why" questions |
| Bloom's Level | Understand, Apply |
| Example Front | How does DHCP differ from DNS? |
| Example Back | DHCP assigns IP addresses dynamically; DNS resolves domain names to IP addresses. |
Type D — Multi-Step Problem
| Element | Description |
|---|
| Front | Problem or calculation |
| Back | Step-by-step solution with reasoning |
| Best for | Numerical problems, derivations, proofs, algorithms |
| Bloom's Level | Apply, Analyze |
| Example Front | Solve: Find the determinant of [[2,3],[1,4]] |
| Example Back | det = (24) - (31) = 8 - 3 = 5 |
Type E — Application Scenario
| Element | Description |
|---|
| Front | Real-world scenario or case snippet |
| Back | Diagnosis, solution, or analysis |
| Best for | Case studies, clinical scenarios, engineering design, business cases |
| Bloom's Level | Analyze, Evaluate |
| Example Front | A user reports "Connection refused" when accessing port 443 on a server. What is likely? |
| Example Back | The service on port 443 (likely HTTPS) is not running or a firewall is blocking the port. |
Type F — Compare & Contrast
| Element | Description | | ----------------- |
--------------------------------------------------------- |
-------------------------------------------------- | | Front | Two related concepts | | Back
| Structured comparison (similarities / differences table) | | Best for | Comparative questions,
distinguishing confusable concepts | | Bloom's Level | Analyze | | Example Front | Compare
TCP vs UDP | | Example Back | TCP: connection-oriented, reliable, ordered, slower | UDP:
connectionless, unreliable, unordered, faster |
2. Difficulty Tiers
| Tier | Question Style | Cognitive Load | Use Case |
|---|
| Tier 1 — Recognition | Multiple choice, true/false, "which of the following" | Low | Initial learning, building confidence |
| Tier 2 — Recall | Direct question, cloze deletion, fill-in-the-blank | Medium | Active recall practice, memory consolidation |
| Tier 3 — Application | Scenario-based, problem-solving, "why/how" questions | High | Deep understanding, exam readiness |
Each deck includes a progression path: Tier 1 -> Tier 2 -> Tier 3.
3. SRS Scheduling Metadata
Every generated flashcard includes these scheduling fields for SRS system import:
| Field | Example | Description |
|---|
Deck | Computer Networks | Subject or chapter name |
Tag | cn_3_transport | Hierarchical topic tag |
Due | 2026-05-24 | Next review date |
Interval | 1 | Days until next review (starts at 1) |
Ease | 250 | Starting ease factor (default 250%) |
Difficulty | 3 | Card difficulty (1=Easy, 5=Hard) |
LastReviewed | 2026-05-23 | Last review timestamp |
4. Export Formats
| Format | Extension | Compatible With | Notes |
|---|
| Anki | .apkg | Anki desktop, AnkiDroid, AnkiMobile | Full SRS metadata preserved |
| CSV | .csv | Anki import, Quizlet, Excel, custom tools | Tab-separated by default |
| Markdown | .md | Any markdown renderer, Obsidian, Notion | Readable, version-controllable |
| Plain Text | .txt | Any text editor | Minimal formatting |
| JSON | .json | Programmatic processing | Structured data export |
International Export Examples
Example CSV Header
Front, Back, Tags, Deck, Due
Example Quizlet Import Format
| Front | Back | Tags |
|---|
| What is TCP? | Transmission Control Protocol | cn_unit3 |
| Define OSI model | 7-layer conceptual model | cn_unit1 |
JSON Export Schema
{
"deck": "Subject_Unit",
"cards": [
{
"front": "Question text",
"back": "Answer text",
"tags": ["tag1", "tag2"],
"due": "2026-06-01",
"interval": 1,
"ease": 250,
"difficulty": 3
}
]
}
Anki APKG Packaging Note
APKG files are SQLite databases with a collection.anki21 table containing the card/note data and a
media directory for images/audio. The system generates APKG-format output compatible with Anki 2.1+.
Import via: Anki Desktop → File → Import → Select .apkg file.
5. Generation Modes
Mode 1 — From Lecture Notes
- Input: Raw notes or textbook chapters
- Output: Comprehensive deck covering all key concepts
- Algorithm: Extract definitions, named concepts, lists, important figures, and causal relationships
Mode 2 — From Syllabus
- Input: Syllabus topics and subtopics
- Output: Coverage-optimized deck ensuring every syllabus point has at least one card
- Algorithm: Map syllabus items to question templates
Mode 3 — From PYQs
- Input: Previous year question papers
- Output: Exam-focused deck targeting historically tested concepts
- Algorithm: Frequency-weight topics and generate cards proportional to historical importance
Mode 4 — Exam Cram
- Input: High-priority topics (from imp topics analysis)
- Output: Condensed deck covering only high-probability questions
- Algorithm: Selects Tier 1 and Tier 2 cards for fastest coverage
6. Deck Organization
Subject Name/
Unit 1 - Topic Name/
Section 1.1 - Subtopic/
[F] Definition of concept X
[C] Cloze: The three types of Y are ___
[P] Problem: Calculate Z given W
Section 1.2 - Subtopic/
...
Unit 2 - Topic Name/
...
Cross-Unit Connections/
[A] How does concept A from Unit 1 relate to concept B from Unit 3?
Prefix legend: [F] = Fact, [C] = Cloze, [P] = Problem, [A] = Association, [S] = Scenario
7. Active Recall Triggers
For each card, the system adds memory-triggering cues:
- Visual cues: Parent diagram references "(see Fig 3.2 in textbook)"
- Mnemonic triggers: Acronym hints (e.g., "PEMDAS: Parentheses, Exponents...")
- Association chains: "This concept is related to X which you studied in Unit 2"
- Contrast prompts: "Not to be confused with Y (see card #42)"
8. Common Use Cases
| Scenario | Mode | Card Types | Deck Size (approx) |
|---|
| Learning a new subject | From Lecture Notes | A, B, C | 200-500 cards |
| Exam revision (1 week) | From PYQs + Syllabus | A, B, D | 100-300 cards |
| Last-night cramming | Exam Cram | A, B | 50-100 cards |
| Language vocabulary | From Lecture Notes | A, B | 500-1000 cards |
| Medical/legal memorization | From Syllabus | A, B, C, E | 500-2000 cards |
| Formula revision | From Syllabus | D | 30-100 cards |
9. Example
User: Generate flashcards for Computer Networks Unit 3 (Transport Layer) for SPPU TE Comp.
Include TCP, UDP, congestion control.
System generates:
Deck: SPPU_TE_CN_Unit3
Card 1 [F]: What does TCP stand for?
Back: Transmission Control Protocol
Card 2 [C]: {{c1::TCP}} is connection-oriented, while {{c2::UDP}} is connectionless.
Card 3 [D]: A sender uses AIMD with cwnd=16 MSS. After packet loss, what is the new cwnd in TCP Reno?
Back: cwnd = 16/2 = 8 MSS (multiplicative decrease)
Card 4 [E]: A video streaming app uses UDP. Why?
Back: Streaming tolerates minor packet loss but requires low latency. UDP provides faster delivery without retransmission delays.
... (full deck generated)
10. Export Command (for Anki)
# The generated .apkg file can be imported via:
# Anki Desktop: File > Import > Select .apkg
# AnkiDroid: Tap + > Import .apkg
# AnkiMobile: Share > Open in Anki
# CSV format follows Anki's preferred tab-separated schema:
# Front\tBack\tTags\tDeck
Session Config
This skill integrates with the session config system (deps/session-profile.json). Before
executing, check for an existing session profile:
- If
deps/session-profile.json exists, read university, subject, pattern, and exam_type
fields to auto-configure the skill.
- If the file does not exist, fall back to user-provided context or prompt the user to run
setup-exam-prompt (or npm run init) first.
- Session config eliminates redundant context detection — detection happens once and is reused
across all skill calls.
Error Handling
| Situation | Action |
|---|
| Source material too short | Respond: "Material too sparse for flashcard generation. Minimum of 500 characters of meaningful content required." |
| Unsupported file format | Respond: "Unsupported format. Accepted formats: PDF, DOCX, TXT, MD, or pasted text." |
| SRS metadata conflict | Auto-resolve by prioritizing session config defaults over card-level overrides |
| Export format failure | Log error, fall back to Markdown export, notify user of format limitation |
Quality Gate — Check Before Output
11. Integration with Other Skills
| Skill | Integration |
|---|
| universal-session-config | Reads university/subject/pattern from session profile |
| universal-notes-generator | Takes generated notes as input and converts them to flashcards |
| universal-pyq-analyzer | Uses PYQ frequency analysis to weight card importance |
| universal-imp-topics-generator | Generates cram-mode decks from imp topics output |
| universal-mcq-practice-generator | Creates exam-simulated MCQ practice from same material |
