docs(evals): S01–S10 标注集 v1、评测工具和评测报告

- evals/gold：1,887 个标注单元（AI 标注、逐条裁定，未经人工复核），规范见 GUIDELINES.md
- prepare / run_all / score / gold：导出文字层、批量抽取、打分、标注定位
- docs/architecture/extract-eval.md：修复前后的结果（三项目标全部达标）和剩余问题
- decisions.md 记 M1（只用 Flash）和 Q1–Q4；架构 §13 SK13；AGENTS.md 进度

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

evals/prepare.py

@@ -0,0 +1,58 @@
+"""准备标注集评测的输入：S01–S10 转成规范化 PDF，导出带句子编号的全文（给人工标注用）。
+
+用法（在 server/ 下）：
+  ../.venv/bin/python ../evals/prepare.py [S01 S02 ...]
+输出 evals/out/docs/<ID>/：normalized.pdf、sentences.txt（每行 `[p12s3] 句子`，带格式标记和〔上级：…〕）。
+规范化 PDF 生成一次后复用，抽取评测（run_extract.py）也用它作输入，标注和评测看到的是同一份文字层。
+"""
+
+from __future__ import annotations
+
+import asyncio
+import pathlib
+import sys
+
+from bid_doctor.checklist import extract
+from bid_doctor.document import formats
+from bid_doctor.document.pipeline import convert, structure, text_layer
+
+ROOT = pathlib.Path(__file__).resolve().parent
+SAMPLES = ROOT.parent / "samples" / "tenders"
+OUT = ROOT / "out" / "docs"
+
+
+async def prepare(doc_id: str) -> None:
+    out = OUT / doc_id
+    out.mkdir(parents=True, exist_ok=True)
+    pdf_path = out / "normalized.pdf"
+    if not pdf_path.exists():
+        src = next(p for p in (SAMPLES / doc_id).iterdir() if p.suffix in (".doc", ".docx", ".pdf"))
+        raw = src.read_bytes()
+        fmt = formats.detect(raw, src.name).format
+        pdf_path.write_bytes(raw if fmt == "pdf" else await convert.to_pdf(raw, fmt))
+    pages = text_layer.extract("D", pdf_path.read_bytes())
+    body = text_layer.body_sentences(pages)
+    parents = structure.parents(body)
+    notes = extract.marking_notes(body)
+    lines = [f"# {doc_id}：{len(pages)} 页，正文句子 {len(body)}", "## 标注规则说明（规则识别）"]
+    lines += [f"- [p{n.sentence.page_no}s{n.sentence.seq}] {n.sentence.text}" for n in notes] or ["（无）"]
+    page = 0
+    for s in body:
+        if s.page_no != page:
+            page = s.page_no
+            lines.append(f"\n=== 第 {page} 页")
+        line = f"[p{s.page_no}s{s.seq}] {s.marked}"
+        if p := parents.get(s.key):
+            line += f"〔上级：{p.text[:40]}〕"
+        lines.append(line)
+    (out / "sentences.txt").write_text("\n".join(lines) + "\n")
+    print(doc_id, len(pages), "页", len(body), "句")
+
+
+async def main() -> None:
+    ids = sys.argv[1:] or [f"S{i:02d}" for i in range(1, 11)]
+    for doc_id in ids:
+        await prepare(doc_id)
+
+
+asyncio.run(main())