第 1 卷三集全部转为成稿（分块扩写 + AI 腔定点返修），文档同步

- 每集两稿：NNN-….md 为成稿（9492/11260/11869 字），NNN-….skeleton.md 为过闸门的骨架稿
- 新增 expand.repair_style：只重写含 AI 腔标记的段落（本例出现了 14 处破折号），
  三集硬伤密度 1.2/1.0/1.5 → 0.1/0.3/0.0（每千字）
- episode 命令接入定点返修；expand 命令保留 A/B 对照用法
- README 同步文笔层、本土化、子命令、以及本轮新踩的坑（\b 盲点、枚举大小写、自制小节标记）
- 第 3 集骨架连换三条线索仍未过闸门（真实拒绝），其成稿基于既有骨架扩写

dfannals/cli.py

@@ -212,6 +212,8 @@ def _expand_in_place(volume: int, world: legends.World, produced, args) -> str:
         for note in fixed.notes:
             print("  " + note)
 
+    text = _polish(text, world, produced.selection.thread, produced.episode, args.model)
+
     produced.path.write_text(text.strip() + "\n", encoding="utf-8")
     remaining = factcheck.check(text, world)
     print(expand_mod.compare(produced.text, text))
@@ -221,6 +223,20 @@ def _expand_in_place(volume: int, world: legends.World, produced, args) -> str:
     return text
 
 
+def _polish(text: str, world, thread, episode, model: str, max_rounds: int = 2) -> str:
+    """定点返修 AI 腔标记（破折号、「不是A而是B」等），只改命中的段落。"""
+    for round_no in range(1, max_rounds + 1):
+        if not expand_mod.style_targets(text):
+            return text
+        result = expand_mod.repair_style(world, thread, episode, text, model=model)
+        for note in result.notes:
+            print(f"  （第 {round_no} 轮）{note}")
+        if result.text == text:
+            return text
+        text = result.text
+    return text
+
+
 def cmd_episode(args: argparse.Namespace) -> int:
     world, found = _load_candidates(args)
     state = chronicle.State.load()

dfannals/expand.py

@@ -320,6 +320,79 @@ def _parse_numbered(raw: str) -> dict[int, str]:
     return {k: v for k, v in out.items() if v}
 
 
+STYLE_FIX_SPEC = """你在做一件很窄的事：清掉正文里的 AI 腔标记，其他内容一律不动。
+
+要清掉的：
+- 破折号「——」与省略号「……」：改成句号、逗号、短句或动作断句；
+- 「不是A，而是B」句式：直接写 B；
+- 「，带着……」这类万能状语；
+- 「他/他知道／明白／意识到／感到」这类直述认知：改成动作或台词；
+- 仿佛／犹如／一丝／一抹／心中一震／眼中闪过／深吸一口气 等禁用词：换成具体描写。
+
+不许增删情节，不许改动没被点到的句子，不许合并或拆分段落。
+只输出改好的段落，每段以 [序号] 开头，序号与段数必须和输入一致。不写任何解释。
+"""
+
+
+def _apply_fixes(text: str, targets: list[int], reply: str) -> tuple[str, int]:
+    """把模型返回的 `[n] 段落` 写回原位；段号对不上就跳过，宁可不改。"""
+    paragraphs = text.split("\n")
+    fixed = _parse_numbered(reply)
+    applied = 0
+    for n, index in enumerate(targets, 1):
+        if n in fixed:
+            paragraphs[index] = fixed[n]
+            applied += 1
+    return "\n".join(paragraphs), applied
+
+
+def style_targets(text: str, limit: int = 8) -> list[int]:
+    """挑出含 AI 腔硬伤的段落（最多 limit 段）。"""
+    targets: list[int] = []
+    for index, para in enumerate(text.split("\n")):
+        if not para.strip():
+            continue
+        if any(hit.level == "hard" for hit in deslop.check(para)):
+            targets.append(index)
+    return targets[:limit]
+
+
+def repair_style(
+    world: World,
+    thread: Thread,
+    episode: ep_mod.Episode,
+    text: str,
+    *,
+    gateway=None,
+    model: str = LITERARY_MODEL,
+    limit: int = 8,
+) -> Normalized:
+    """定点清掉 AI 腔标记，只重写命中的段落。
+
+    实测：一次扩写能冒出 14 处破折号（提示词里明确禁用也拦不住）。
+    确定性地把「——」一律换成逗号会读着别扭，所以交回模型改，但只改命中的段。
+    """
+    targets = style_targets(text, limit)
+    if not targets:
+        return normalize(text)
+    paragraphs = text.split("\n")
+    numbered = "\n".join(f"[{n}] {paragraphs[i]}" for n, i in enumerate(targets, 1))
+    messages = [
+        {"role": "system", "content": STYLE_FIX_SPEC},
+        {"role": "user", "content": "\n".join([
+            "### 允许使用的专名", "", "、".join(allowed_names(world, thread, episode)), "",
+            "### 全文的 AI 腔诊断", "", deslop.digest(text, top=12), "",
+            f"### 需要改的段落（共 {len(targets)} 段）", "", numbered, "",
+            f"### 要求：只输出改好的 {len(targets)} 段，每段以 [序号] 开头。",
+        ])},
+    ]
+    reply = chat(messages, gateway=gateway, model=model, max_tokens=MAX_TOKENS_EXPAND).content
+    fixed_text, applied = _apply_fixes(text, targets, reply)
+    result = normalize(fixed_text)
+    result.notes = [f"AI 腔定点返修：改写 {applied}/{len(targets)} 段"] + result.notes
+    return result
+
+
 def repair_names(
     world: World,
     thread: Thread,
@@ -353,15 +426,9 @@ def repair_names(
         ])},
     ]
     reply = chat(messages, gateway=gateway, model=model, max_tokens=MAX_TOKENS_EXPAND).content
-    fixed = _parse_numbered(reply)
+    fixed_text, applied = _apply_fixes(text, targets, reply)
 
-    applied = 0
-    for n, index in enumerate(targets, 1):
-        if n in fixed:
-            paragraphs[index] = fixed[n]
-            applied += 1
-
-    result = normalize("\n".join(paragraphs))
+    result = normalize(fixed_text)
     result.notes = [f"可疑专名修复：改写 {applied}/{len(targets)} 段"] + result.notes
     return result