文笔层：AI 味机检、标点规范化、分块大量扩写（第 1 集成稿 10805 字）

- 修复上次提交把 dfannals/cli.py 写成 0 字节的问题（它是唯一入口，导致管道不可运行） - 性别：解析 <caste>，人物表与写作素材带性别（Ral Fastenhatchets 实为女性） - 新增 dfannals/deslop.py：AI 味机械诊断（硬伤词/句式/标点，按千字密度报告） - 新增 dfannals/normalize.py：标点与结构清理（引号配对、重复段落与句子、模型自加的小节标记） - 新增 dfannals/expand.py 与 prompts/literary-expander.md：按年份场景分块大量扩写 - 专名防幻觉：每块附史料专名白名单，事后按段自动修复可疑专名 - episode 命令并进文笔层（骨架稿另存 .skeleton.md），新增 expand 命令做 A/B 对照 - 新增 notes/switched-threads.md 与 test_deslop / test_normalize 回归测试 - 提交前拦截「已跟踪文件为空」，防止上述事故复发
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+"""AI 味机械诊断：把「文笔是否自然」变成可度量的指标。
+
+规则来自 oh-story-claudecode 的 story-deslop 与 banned-words（MIT），做了两处适配：
+
+1. **分层**。原文把「仿佛、一丝、坚定、冰冷」放同一张一级表，但「坚定」「冰冷」在
+   史书叙事里是正常词（矮人要塞的"冰冷"可能是字面温度），一律判罪会刷满假阳性。
+   因此分成硬伤词（几乎只在 AI 文本里成串出现）与密度词（真人也用，只看密度）。
+2. **按密度而非布尔判定**。AI 味是密度问题：出现一次是风格，出现二十次是模板。
+   输出「每千字命中数」，供闸门与扩写模型参考。
+
+语义类判断（比喻是否套话、是否把一件事掰成三段写）机械检查假阳性太高，
+交给扩写模型和自评闸门，这里不猜。
+"""
+from __future__ import annotations
+
+import re
+from dataclasses import dataclass, field
+
+from dfannals.chronicle import cjk_length
+
+# 硬伤词：出现在正常中文里的概率很低，命中一处就该改
+HARD_WORDS: dict[str, tuple[str, ...]] = {
+    "情态": ("仿佛", "犹如", "宛若", "如同", "一丝", "一抹", "些许", "几分", "隐约",
+             "毫无征兆", "几不可闻", "微不可察"),
+    "动作": ("深吸一口气", "不禁"),
+    "表情": ("眼中闪过", "嘴角勾起", "眉头微皱", "眉眼低垂", "瞳孔微缩", "瞳孔收缩",
+             "瞳孔一缩", "指节泛白", "眼神锐利", "目光锐利"),
+    "心理": ("心中一动", "心头一震", "心下了然", "心中暗道", "心底泛起", "不由得", "心中一凛"),
+    "判断": ("不容置疑", "不容置喙", "不易察觉", "显而易见", "毫无疑问", "不可否认", "前所未有"),
+    "过渡": ("不由自主", "情不自禁", "自然而然", "话锋一转", "闪烁着光芒"),
+}
+
+# 密度词：真人写作也用，只有成串出现才算模板腔
+SOFT_WORDS: dict[str, tuple[str, ...]] = {
+    "形容": ("坚定", "狡黠", "深邃", "凛冽", "冰冷"),
+    "语境敏感": ("突然", "陡然", "骤然", "猛然", "好像", "似乎", "瞬间", "猛地", "死死地"),
+    "弱化副词": ("缓缓", "微微", "轻轻", "淡淡"),
+}
+
+# 句式与标点：每条是（规则名，说明，正则）
+PATTERNS: tuple[tuple[str, str, str], ...] = (
+    ("不是A而是B", "最毒的 AI 句式，直接写 B", r"不是[^，。；！？\n]{1,24}[，,]\s*(?:而)?是"),
+    ("万能动宾", "「，带着……」万能状语", r"[，,]\s*带着[^，。；！？\n]{0,20}"),
+    ("声音描写", "「声音不大，却带着……」", r"声音(?:不大|很轻|很平|平静)[^。\n]{0,14}(?:却|但)?带着"),
+    ("认知直述", "告诉而非展示，改为动作或台词", r"(?:他|她|他们|她们)(?:这才|终于)?(?:明白|意识到|感到|知道)"),
+    ("章末预告", "「他不知道的是……」空泛预告", r"(?:他|她)不知道的是"),
+    ("收束腔", "「这一刻／才刚刚开始」式总结", r"这一刻[，,]|从这一刻开始|才刚刚开始|原来[，,]"),
+    ("抽象命运", "命运＋齿轮／棋局／獠牙", r"命运[^。\n]{0,8}(?:齿轮|棋局|獠牙|改写|安排)"),
+    ("心理模板", "「心中一震／心头一凛」式心理惊吓", r"心(?:中|头|底)(?:一|猛|顿)(?:震|凛|颤)"),
+    ("过渡模板", "「取而代之的是」", r"取而代之"),
+    ("告诉而非展示", "「显得有些X」「散发着一股X气息」", r"显得(?:有些|十分|非常)?[\u4e00-\u9fff]{1,4}|散发(?:着|出)?[^。\n]{0,8}(?:气息|气场)"),
+    ("公式化对话标签", "「好的，他说道」", r"[，,](?:他|她)(?:说道|开口道|沉声道|低声道)"),
+    ("英文引号", "模型常直接吐 ASCII 直角引号，中文排版用“”", r'"'),
+    ("破折号", "正文禁用，改用句号、逗号或动作断句", r"——|──|(?<!-)--(?!-)"),
+    ("省略号", "正文禁用，用动作或短句表达停顿", r"……|\.\.\."),
+)
+
+SAMPLE_WIDTH = 14
+SAMPLES_PER_RULE = 2
+
+
+@dataclass
+class Hit:
+    """一条诊断：命中哪个规则、几次、原文长什么样。"""
+
+    rule: str
+    category: str
+    level: str          # hard = 硬伤词+句式+标点；soft = 只看密度的词
+    count: int
+    samples: list[str] = field(default_factory=list)
+
+    def line(self) -> str:
+        ex = "；".join(self.samples)
+        return f"{self.category:<6} {self.rule:<8} ×{self.count:<3} {ex}"
+
+
+def _context(text: str, start: int, end: int) -> str:
+    left = max(0, start - SAMPLE_WIDTH)
+    right = min(len(text), end + SAMPLE_WIDTH)
+    return text[left:right].replace("\n", " ").strip()
+
+
+def _scan_word(text: str, word: str) -> tuple[int, list[str]]:
+    count, samples, pos = 0, [], text.find(word)
+    while pos != -1:
+        count += 1
+        if len(samples) < SAMPLES_PER_RULE:
+            samples.append(_context(text, pos, pos + len(word)))
+        pos = text.find(word, pos + len(word))
+    return count, samples
+
+
+def check(text: str) -> list[Hit]:
+    """扫一遍文本，返回全部诊断（硬伤在前，同类按命中数降序）。"""
+    hits: list[Hit] = []
+
+    for category, words in HARD_WORDS.items():
+        for word in words:
+            count, samples = _scan_word(text, word)
+            if count:
+                hits.append(Hit(word, category, "hard", count, samples))
+
+    for rule, _note, pattern in PATTERNS:
+        rx = re.compile(pattern)
+        found = list(rx.finditer(text))
+        if found:
+            samples = [_context(text, m.start(), m.end()) for m in found[:SAMPLES_PER_RULE]]
+            hits.append(Hit(rule, "句式" if not rule.startswith(("破折号", "省略号", "英文引号")) else "标点",
+                            "hard", len(found), samples))
+
+    for category, words in SOFT_WORDS.items():
+        for word in words:
+            count, samples = _scan_word(text, word)
+            if count:
+                hits.append(Hit(word, category, "soft", count, samples))
+
+    hits.sort(key=lambda h: (h.level != "hard", -h.count, h.rule))
+    return hits
+
+
+def hard_hits(hits: list[Hit]) -> list[Hit]:
+    return [h for h in hits if h.level == "hard"]
+
+
+def per_k(text: str) -> float:
+    """每千字硬伤命中数。空文本返回 0，避免除零。"""
+    length = cjk_length(text) or 1
+    return sum(h.count for h in hard_hits(check(text))) * 1000 / length
+
+
+def report(text: str, hits: list[Hit] | None = None, top: int = 14) -> str:
+    hits = check(text) if hits is None else hits
+    hard = hard_hits(hits)
+    soft = [h for h in hits if h.level == "soft"]
+    total_hard = sum(h.count for h in hard)
+    total_soft = sum(h.count for h in soft)
+    length = cjk_length(text)
+    density = total_hard * 1000 / (length or 1)
+
+    lines = [
+        f"AI 味诊断：{length} 字｜硬伤 {total_hard} 处（{density:.1f}/千字）｜密度词 {total_soft} 处",
+    ]
+    if hard:
+        lines.append("")
+        lines.append("硬伤（命中即改）：")
+        lines += ["  " + h.line() for h in hard[:top]]
+    if soft:
+        lines.append("")
+        lines.append("密度词（成串才处理）：")
+        lines += ["  " + h.line() for h in soft[:top]]
+    if not hard and not soft:
+        lines.append("  没有命中：用词干净。")
+    return "\n".join(lines)
+
+
+def digest(text: str, top: int = 10) -> str:
+    """给扩写模型看的简短诊断：要求它逐条消灭这些。"""
+    hits = [h for h in check(text) if h.level == "hard"][:top]
+    if not hits:
+        return "（机械检查没有发现 AI 味硬伤；重点放在把概述换成场景。）"
+    return "\n".join(f"- {h.category}『{h.rule}』×{h.count}｜例：{h.samples[0] if h.samples else ''}"
+                     for h in hits)