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Generates CIOMS I-compliant ICSR narratives from adverse event case data for FDA and EMA regulatory submission. Includes temporal analysis, MedDRA coding, causality assessment using WHO-UMC or Naranjo criteria, and multi-format output.
Use when determining author order on research manuscripts, assigning CRediT contributor roles for transparency, documenting individual contributions to collaborative projects, or resolving authorship disputes in multi-institutional research. Generates fair and transparent auth...
Generate structured SOAP notes from clinical narratives, transcripts, or existing notes; use when the user needs de-identified clinical documentation organized into Subjective, Objective, Assessment, and Plan sections, with clear assumptions and review points.
基于 SOC 职业分类
正在显示 SKILL.md
| name | anatomy-quiz-master |
| description | Generate interactive anatomy quizzes for medical education with multiple. |
| license | MIT |
| author | AIPOCH |
scripts/main.py.references/ for task-specific guidance.Python: 3.10+. Repository baseline for current packaged skills.argparse: unspecified. Declared in requirements.txt.json: unspecified. Declared in requirements.txt.random: unspecified. Declared in requirements.txt.See ## Usage above for related details.
cd "20260318/scientific-skills/Academic Writing/anatomy-quiz-master"
python -m py_compile scripts/main.py
python scripts/main.py --help
Example run plan:
CONFIG block or documented parameters if the script uses fixed settings.python scripts/main.py with the validated inputs.See ## Workflow above for related details.
scripts/main.py.references/ contains supporting rules, prompts, or checklists.Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.py
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/main.py --help
Comprehensive anatomy education tool that generates interactive quizzes covering gross anatomy, neuroanatomy, and clinical anatomy with adaptive difficulty and detailed explanations.
Key Capabilities:
Generate focused quizzes by body region:
from scripts.quiz_generator import QuizGenerator
generator = QuizGenerator()
# Generate thorax quiz
quiz = generator.generate_quiz(
region="thorax",
topics=["heart", "lungs", "mediastinum", "thoracic_wall"],
difficulty="intermediate",
n_questions=20
)
# Export for LMS
quiz.export(format="json", filename="thorax_quiz.json")
Supported Regions:
| Region | Subtopics | Question Types |
|---|---|---|
| Head & Neck | Skull, cranial nerves, triangles, viscera | Identification, pathways, clinical |
| Thorax | Heart, lungs, mediastinum, pleura | Relations, auscultation, imaging |
| Abdomen | GI tract, retroperitoneum, vessels | Peritoneal reflections, vascular supply |
| Pelvis | Organs, perineum, walls | Gender differences, clinical correlations |
| Upper Limb | Shoulder, arm, forearm, hand | Muscle actions, innervation, clinical |
| Lower Limb | Hip, thigh, leg, foot | Gait, compartments, clinical exams |
| Back | Vertebral column, spinal cord, muscles | Levels, landmarks, clinical |
Specialized quizzes for neural pathways:
# Neuroanatomy quiz
neuro_quiz = generator.generate_neuro_quiz(
pathway_type="motor", # or "sensory", "cranial_nerves", "reflexes"
include_lesions=True,
clinical_correlations=True
)
Pathway Types:
Integrate anatomy with clinical scenarios:
clinical_quiz = generator.generate_clinical_quiz(
region="abdomen",
scenario_types=["surgery", "radiology", "physical_exam"],
difficulty="advanced"
)
Question Formats:
Clinical Scenario:
"A 45-year-old male presents with epigastric pain radiating to the back.
CT shows a mass in the lesser sac."
Question: "Which artery runs immediately posterior to the body of the
pancreas and would be at risk during resection?"
A) Splenic artery
B) Superior mesenteric artery
C) Common hepatic artery
D) Left gastric artery
Correct: B) Superior mesenteric artery
Explanation: The SMA emerges from the aorta at L1 and passes posterior
to the neck of the pancreas and anterior to the uncinate process...
Adjust difficulty based on performance:
from scripts.adaptive import AdaptiveEngine
engine = AdaptiveEngine()
# Track student performance
student_progress = engine.track_performance(
student_id="student_001",
quiz_results=results,
time_per_question=True
)
# Generate personalized quiz targeting weak areas
personalized = engine.generate_adaptive_quiz(
student_progress=student_progress,
focus_areas=["thorax_vessels", "cranial_nerves"],
mastery_threshold=0.80
)
Question Quality:
Educational Value:
Technical Quality:
Before Use:
Content Issues:
❌ Outdated anatomical knowledge → Teaching old terminology
❌ Nit-picky details → Testing obscure structures rarely clinically relevant
❌ Unclear images → Poor resolution or confusing labels
Educational Issues:
❌ Questions too easy → No learning benefit
❌ No clinical context → Pure memorization without application
❌ Punitive difficulty → Discouraging rather than challenging
Technical Issues:
❌ Predictable patterns → Students game the system
❌ No progress tracking → Can't identify weak areas
Available in references/ directory:
netter_atlas_correlation.md - Question-to-atlas page mappingterminologia_anatomica.md - Standard anatomical terminologyusmle_content_outline.md - NBME anatomy topic frequenciesclinical_correlations.md - High-yield clinical anatomy scenariosimage_sources.md - Licensed anatomical image repositoriesdifficulty_calibration.md - Bloom's taxonomy level alignmentLocated in scripts/ directory:
main.py - CLI for quiz generationquiz_generator.py - Core question generation engineneuro_quiz.py - Specialized neuroanatomy questionsclinical_correlator.py - Clinical scenario integrationadaptive_engine.py - Personalized difficulty adjustmentimage_quiz.py - Label identification with imagesprogress_tracker.py - Performance analyticsreport_generator.py - Progress reports and statistics| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--region, -r | string | upper_limb | No | Anatomical region (upper_limb, lower_limb, thorax, abdomen, pelvis, head_neck, neuroanatomy) |
--difficulty, -d | string | intermediate | No | Difficulty level (basic, intermediate, advanced) |
--count, -c | int | 1 | No | Number of questions to generate |
--output, -o | string | - | No | Output file path (JSON format) |
--format | string | json | No | Output format (json or text) |
--list-regions | flag | - | No | List all available regions and exit |
# Generate single question
python scripts/main.py --region upper_limb
# Generate 10-question quiz
python scripts/main.py --region neuroanatomy --difficulty advanced --count 10 --output quiz.json
# List available regions
python scripts/main.py --list-regions
# Text format output
python scripts/main.py --region thorax --format text
Every final response should make these items explicit when they are relevant:
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.This skill accepts requests that match the documented purpose of anatomy-quiz-master and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
anatomy-quiz-masteronly handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Use the following fixed structure for non-trivial requests:
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.