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考古題分析器，分析歷屆考題的出題模式和重點分布。Triggers: 考古題分析, 歷屆考題, past exam, 考古題, 歷屆, 出題模式, 考題分析.
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MCP tools for PDF ingestion → extract figures, tables, sections → build knowledge graph. Transforms PDF into queryable assets (images, tables, text) with cross-document RAG. Triggers: PDF, ingest, extract, 圖片, 表格, figure, table, manifest, knowledge graph, 知識圖譜, RAG, 文獻分析.
難度分類器，基於 Ragas 標準評估題目難度。Triggers: 難度分類, 難度評估, difficulty, 評估難度, 調整難度.
重複題目檢查器，檢測語意重複和過度相似的題目。Triggers: 查重, 重複檢查, duplicate, 相似題, 題目查重, 檢查重複.
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| name | past-exam-analyzer |
| description | 考古題分析器，分析歷屆考題的出題模式和重點分布。Triggers: 考古題分析, 歷屆考題, past exam, 考古題, 歷屆, 出題模式, 考題分析. |
分析歷屆考題，識別：
這對於預測考試重點和設計模擬考非常有用。
def load_past_exams(years=5):
"""載入近 N 年的考古題"""
exams = exam-generator__exam_get_past_exam(
exam_type="board", # 專科考試
years=years
)
return exams
def analyze_topic_distribution(exams):
"""分析各主題的出題頻率"""
topic_counts = defaultdict(int)
for exam in exams:
for question in exam.questions:
for topic in question.topics:
topic_counts[topic] += 1
# 計算比例
total = sum(topic_counts.values())
distribution = {
topic: count / total
for topic, count in topic_counts.items()
}
return sorted(distribution.items(), key=lambda x: -x[1])
def calculate_importance_score(topic, exams):
"""計算主題重要性分數"""
# 因素權重
frequency_weight = 0.4 # 出現頻率
recency_weight = 0.3 # 近期是否出現
consistency_weight = 0.2 # 是否每年都考
difficulty_weight = 0.1 # 平均難度
freq = topic_frequency(topic, exams)
recency = topic_recency(topic, exams)
consistency = topic_consistency(topic, exams)
difficulty = topic_avg_difficulty(topic, exams)
score = (
freq * frequency_weight +
recency * recency_weight +
consistency * consistency_weight +
difficulty * difficulty_weight
)
return score
def analyze_trends(exams):
"""分析出題趨勢"""
yearly_data = group_by_year(exams)
trends = {
"rising_topics": [], # 出題頻率上升
"declining_topics": [], # 出題頻率下降
"stable_topics": [], # 穩定出現
"new_topics": [], # 新出現的主題
"difficulty_trend": None # 難度趨勢
}
return trends
{
"exam_type": "麻醉專科醫師考試",
"years_analyzed": 5,
"total_questions": 500,
"topic_distribution": [
{"topic": "藥理學", "percentage": 25.4, "questions": 127},
{"topic": "呼吸管理", "percentage": 18.2, "questions": 91},
{"topic": "心血管監測", "percentage": 15.6, "questions": 78},
{"topic"
📊 考古題分析報告
考試類型: 麻醉專科醫師考試
分析範圍: 2021-2025 (5年)
題目總數: 500 題
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔥 高頻出題主題 (Top 10)
排名 主題 比例 題數 重要性
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1 藥理學 25.4% 127 ⭐⭐⭐⭐⭐
2 呼吸管理 18.2% 91 ⭐⭐⭐⭐⭐
3 心血管監測 15.6% 78 ⭐⭐⭐⭐
4 區域麻醉 12.8% 64 ⭐⭐⭐⭐
5 神經生理 8.4% 42 ⭐⭐⭐
...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 出題趨勢
上升趨勢 (近年出現更多):
├── 🆕 ERAS (Enhanced Recovery)
├── 🆕 術後認知功能障礙 (POCD)
└── 🆕 超音波引導區域麻醉
下降趨勢:
├── 📉 傳統解剖定位技術
└── 📉 吸入誘導
穩定出現 (每年必考):
├── ✓ 藥物動力學基本概念
├── ✓ 監測原理
└── ✓ 緊急狀況處理
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📉 難度趨勢
2021: ████████████░░░░░░░░ 62%
2022: █████████████░░░░░░░ 65%
2023: ██████████████░░░░░░ 68%
2024: ███████████████░░░░░ 71%
2025: ████████████████░░░░ 預估 73%
趨勢: 逐年增加 (+2.3%/年)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 出題預測 (2026)
高機率出現:
├── Propofol 藥理 (連續5年)
├── Succinylcholine 禁忌症 (連續5年)
├── 惡性高熱處理 (連續4年)
└── 困難呼吸道演算法 (連續5年)
新興主題 (建議準備):
├── 術中神經監測 (近2年新增)
├── 目標導向輸液治療 (GDFT)
└── 麻醉深度監測 (BIS/Entropy)
歷年易錯題型:
├── 藥物交互作用計算
├── 評分量表解讀 (ASA, Mallampati)
└── 圖表判讀 (藥物濃度曲線)