Anki Card Creator

Anki Card Creator

Overview

Intelligent flashcard generation tool that transforms medical study materials into Anki-compatible cards optimized for long-term retention through evidence-based spaced repetition.

Key Capabilities:

When to Use

✅ Use this skill when:

❌ Do NOT use when:

Integration:

Core Capabilities

1. Cloze Deletion Generation

Create fill-in-the-blank cards from dense text:

from scripts.card_creator import AnkiCardCreator
creator = AnkiCardCreator()
Generate cloze cards from text
text = """
Acute inflammation is characterized by five cardinal signs: 
redness (rubor), heat (calor), swelling (tumor), pain (dolor), 
and loss of function (functio laesa). These result from 
vasodilation, increased vascular permeability, and leukocyte 
infiltration.
"""
cards = creator.create_cloze_cards(
    text=text,
    n_cards=3,  # Generate 3 cards from this text
    difficulty="intermediate",
    tags=["Pathology", "Inflammation", "General_Pathology"]
)
Output format (Anki-compatible)
Card 1: "Acute inflammation is characterized by {{c1::five}} cardinal signs..."
Card 2: "...signs: {{c1::redness}} (rubor), {{c2::heat}} (calor)..."

Cloze Strategies: | Strategy | Use Case | Example | |----------|----------|---------| | Single Deletion | Key facts | "The {{c1::liver}} is the largest internal organ" | | Multiple Deletions | Lists/groups | "CRAB symptoms: {{c1::Calcium}}, {{c2::Renal}}, {{c3::Anemia}}, {{c4::Bone}}" | | Hierarchical | Progressive detail | "{{c1::Metformin}} is a {{c2::biguanide}} that {{c3::decreases hepatic glucose production}}" |

2. Basic and Reversible Cards

Generate question-answer pairs:

# Create basic cards
cards = creator.create_basic_cards(
    content={
        "What is the mechanism of action of penicillin?": 
            "Inhibition of bacterial cell wall synthesis by binding to PBPs",
        "What are the major side effects of ACE inhibitors?":
            "Dry cough, hyperkalemia, angioedema, hypotension"
    },
    reversible=True,  # Create reverse cards too
    tags=["Pharmacology", "Antibiotics"]
)

Card Types:

3. Image Occlusion Cards

Create visual learning cards from diagrams:

# Image occlusion for anatomy
cards = creator.create_image_occlusion(
    image_path="brachial_plexus.png",
    occlude_regions=[
        {"label": "Musculocutaneous nerve", "coords": (120, 200, 200, 240)},
        {"label": "Median nerve", "coords": (300, 250, 380, 290)},
        {"label": "Ulnar nerve", "coords": (400, 280, 480, 320)}
    ],
    card_type="one_by_one"  # or "all_at_once"
)

Occlusion Types:

4. Smart Tagging and Organization

Automatically organize cards into logical hierarchies:

# Auto-tag based on content
cards = creator.process_textbook_chapter(
    chapter_text=pathoma_chapter,
    source="Pathoma - Hematopoiesis",
    auto_tag=True,
    tag_hierarchy=[
        "Pathoma",
        "{{chapter_name}}",
        "{{section_name}}"
    ]
)
Results in tags like:
Pathoma::Hematopoiesis::Red_Cell_Disorders
Pathoma::Hematopoiesis::White_Cell_Disorders

Tagging Strategies:

Common Patterns

Pattern 1: Textbook Chapter Conversion

Scenario: Convert entire First Aid chapter to Anki deck.

# Extract and convert chapter
python scripts/main.py \
  --input first_aid_cardiology.pdf \
  --chapter "Ischemic Heart Disease" \
  --card-type cloze \
  --n-cards-per-page 3 \
  --tags "First_Aid::Cardiology::IHD" \
  --output ischemic_heart_disease.apkg
Import directly to Anki
File ready for import with media included

Workflow: 1. Read chapter for understanding first 2. Run conversion tool 3. Review generated cards for accuracy 4. Import to Anki 5. Study with standard spaced repetition

Pattern 2: Drug Cards with Images

Scenario: Create comprehensive pharmacology cards.

# Generate drug cards with mechanisms
drugs = [
    {
        "name": "Metformin",
        "class": "Biguanide",
        "mechanism": "Activates AMPK, decreases hepatic gluconeogenesis",
        "indications": "Type 2 diabetes, PCOS",
        "side_effects": "GI upset, lactic acidosis (rare), B12 deficiency",
        "image": "metformin_structure.png"
    }
]
cards = creator.create_drug_cards(
    drugs=drugs,
    include_structures=True,
    include_mechanism_diagrams=True,
    tags=["Pharmacology", "Diabetes", "First_Line"]
)

Card Format:

Front: Metformin - Class?
Back: Biguanide
Tags: Pharmacology::Diabetes::First_Line
Front: Metformin - Mechanism?
Back: Activates AMPK → decreases hepatic gluconeogenesis
Image: [mechanism diagram]
Tags: Pharmacology::Diabetes::Mechanism
Front: Metformin - Side effects?
Back: GI upset, lactic acidosis (rare), B12 deficiency
Tags: Pharmacology::Diabetes::Side_Effects

Pattern 3: Pathology Differential Cards

Scenario: Create cards for differential diagnosis practice.

# Differential diagnosis cards
cards = creator.create_differential_cards(
    condition="Cough with hemoptysis",
    differentials=[
        {"diagnosis": "Lung cancer", "key_features": "Smoker, weight loss, mass on CT"},
        {"diagnosis": "TB", "key_features": "Immigrant, night sweats, cavitary lesion"},
        {"diagnosis": "PE", "key_features": "Sudden onset, tachypnea, D-dimer elevated"},
        {"diagnosis": "Bronchiectasis", "key_features": "Chronic cough, purulent sputum, dilated airways"}
    ],
    card_type="compare_contrast"
)

Card Types:

Pattern 4: Lecture Notes to Cards

Scenario: Convert professor's lecture slides to study cards.

# Process lecture PDF
python scripts/main.py \
  --input lecture_slides.pdf \
  --source "Dr_Smith_Cardiology_Lecture_5" \
  --card-type mixed \
  --extract-images \
  --auto-tag \
  --output cardiology_lecture_5.apkg
Review and edit in Anki
Delete low-yield cards
Add personal mnemonics

Post-Processing Tips:

Complete Workflow Example

Building comprehensive USMLE Step 1 deck:

# Step 1: Process multiple sources
python scripts/main.py \
  --input first_aid_pathology.pdf \
  --source "First_Aid_2024" \
  --card-type cloze \
  --tags "First_Aid::Pathology" \
  --output fa_pathology.apkg
python scripts/main.py \
  --input sketchy_pharm.pdf \
  --source "Sketchy_Pharm" \
  --card-type basic \
  --include-images \
  --tags "Sketchy::Pharm" \
  --output sketchy_pharm.apkg
Step 2: Merge decks
python scripts/main.py \
  --merge fa_pathology.apkg sketchy_pharm.apkg \
  --output usmle_step1_master.apkg
Step 3: Add leech tags for difficult cards
python scripts/main.py \
  --input usmle_step1_master.apkg \
  --tag-leeches \
  --leech-threshold 8 \
  --output usmle_step1_tagged.apkg

Python API:

from scripts.card_creator import AnkiCardCreator
from scripts.importers import PDFImporter
Initialize
creator = AnkiCardCreator()
importer = PDFImporter()
Import and process textbook
content = importer.import_pdf(
    path="robbins_pathologic_basis_of_disease.pdf",
    pages="150-200",  # Inflammation chapter
    extract_images=True
)
Create cloze cards
cards = creator.create_cloze_cards(
    text=content.text,
    images=content.images,
    n_cards=50,
    difficulty="advanced",
    tags=["Robbins", "General_Pathology", "Inflammation"]
)
Add image occlusion for diagrams
for diagram in content.diagrams:
    occlusion_cards = creator.create_image_occlusion(
        image=diagram,
        auto_detect_labels=True
    )
    cards.extend(occlusion_cards)
Export Anki package
creator.export_apkg(
    cards=cards,
    deck_name="Robbins_Inflammation",
    output_path="robbins_inflammation.apkg"
)
print(f"Created {len(cards)} cards ready for Anki import")

Quality Checklist

Card Quality:

Educational Value:

Technical Quality:

Before Study:

Common Pitfalls

Content Issues:

Card Design Issues:

Study Strategy Issues:

References

Available in references/ directory:

Scripts

Located in scripts/ directory:

Limitations

Parameters

| Parameter | Type | Default | Required | Description | |-----------|------|---------|----------|-------------| | --input, -i | string | - | No | Input text file with Q&A pairs | | --output, -o | string | anki_cards.txt | No | Output file (Anki TSV format) | | --drug | flag | - | No | Create drug information card | | --anatomy | flag | - | No | Create anatomy card | | --name | string | - | No | Drug or structure name | | --mechanism | string | - | No | Mechanism of action (for drug cards) | | --indications | string | - | No | Clinical indications (for drug cards) | | --side-effects | string | - | No | Side effects (for drug cards) | | --location | string | - | No | Anatomical location (for anatomy cards) | | --function | string | - | No | Function (for anatomy cards) |

Usage

Basic Usage

# Create drug card
python scripts/main.py --drug --name "Metformin" --mechanism "Decreases hepatic glucose production" --indications "Type 2 diabetes" --output metformin.txt
Create anatomy card
python scripts/main.py --anatomy --name "Coronary arteries" --location "Surface of heart" --function "Supply oxygenated blood to myocardium" --output coronary.txt
Parse Q&A file
python scripts/main.py --input questions.txt --output deck.txt

Input File Format

Q: What is the mechanism of action of Metformin?
A: Decreases hepatic glucose production, increases insulin sensitivity
Q: Which artery supplies the left ventricle?
A: Left anterior descending artery (LAD)

Risk Assessment

| Risk Indicator | Assessment | Level | |----------------|------------|-------| | Code Execution | Python script executed locally | Low | | Network Access | No external API calls | Low | | File System Access | Read input file, write to output file | Low | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output saved only to specified location | Low |

Security Checklist

Prerequisites

# Python 3.7+
No additional packages required (uses standard library)

Evaluation Criteria

Success Metrics

Test Cases

Lifecycle Status

🧠 Study Tip: The best flashcard is one you'll actually review. Create cards for material you genuinely need to memorize, and keep the daily review load sustainable. Quality over quantity—better to deeply learn 1000 cards than superficially memorize 5000.

Basic Usage

# Create drug card
python scripts/main.py --drug --name "Metformin" --mechanism "Decreases hepatic glucose production" --indications "Type 2 diabetes" --output metformin.txt
Create anatomy card
python scripts/main.py --anatomy --name "Coronary arteries" --location "Surface of heart" --function "Supply oxygenated blood to myocardium" --output coronary.txt
Parse Q&A file
python scripts/main.py --input questions.txt --output deck.txt

Input File Format

Q: What is the mechanism of action of Metformin?
A: Decreases hepatic glucose production, increases insulin sensitivity
Q: Which artery supplies the left ventricle?
A: Left anterior descending artery (LAD)

# Python 3.7+
No additional packages required (uses standard library)