验收复核查出的三处：有量纲比率的效应值（结构效应、自身效应、合计影响、变化）照原值显示，不再乘一百说成百分点（客单价影响 -11.12 元 / 单以前显示 -1,112.1 个百分点）；只读一张表、目录还没维护时分析范围照实说目录没维护，不说成对不上目录里的列；写作规则补一条不写重复判定语开头的引言

backend/app/analysis/decompose.py

@@ -693,15 +693,19 @@ def _ratio_result(env: Env, params: dict[str, Any], used: list[str], segs: list[
         values["gap"] = canon(max(gaps.values(), key=abs))
     verdict = {"code": code, "subjects": [_key_strings(x.key) for x in subjects],
                "direction": sign_word(delta) if code in ("mix_driven", "rate_driven", "both") else None}
+    # 显示格式按「这一段（这个数）是占比还是带量纲的比率」分：
+    # - 各段分子都不超过分母时，整体和各段的比率是个占比（退款率）：比率按百分数，结构 / 自身 / 合计影响是比率的变化，
+    #   按百分点
+    # - 否则比率本身带量纲（客单价，元 / 单，可以大于 1）：比率照原值；影响也是同一个量纲的变化（元 / 单），照原值，
+    #   不能乘一百说成「个百分点」——否则判定语写「客单价下降 9.89」、表里同一件事写「-988.7 个百分点」
+    ratio_rate = ("r_base", "r_target") if proportion else ()
+    points = ("mix", "rate", "total") if proportion else ()
+    named_points = ("delta", "mix_total", "rate_total") if proportion else ()
     return build(env, params, used, table=table, values=values, verdict=verdict, criterion=criterion,
                  phrase=ph.with_caveats(main, caveats, skip=("comparability",) if outcome is None else ()),
                  caveats=caveats,
-                 # 权重（占比）按百分数；结构效应、自身效应、合计影响是比率的变化，按百分点。各段的比率和整体比率本身：
-                 # 各段分子都不超过分母时它是个占比（退款率），按百分数；否则它是有量纲的比率（客单价，元 / 单，可以大于 1），
-                 # 照原值显示——一律套百分数会把客单价 160.76 显示成 16,076.0%
-                 formats=_rate_formats(columns, rate=("w_base", "w_target") + (("r_base", "r_target") if proportion else ()),
-                                       points=("mix", "rate", "total")),
-                 named={k: CONV_POINTS for k in ("delta", "mix_total", "rate_total")}
+                 formats=_rate_formats(columns, rate=("w_base", "w_target") + ratio_rate, points=points),
+                 named={k: CONV_POINTS for k in named_points}
                  | ({k: CONV_PCT for k in ("r_base_total", "r_target_total")} if proportion else {})
                  | {"mix_share": CONV_PCT, "rate_share": CONV_PCT})
 

backend/app/engine/analysis_claims.py

@@ -1130,7 +1130,9 @@ ANALYSIS_RULES_PROMPT = (
     "否则写成待核实的推测，比如「可能与促销结束有关，待核实」。\n"
     "- 判定语整句引用（[[a:A1]]）时一句只引用一份结论，不要把几份不同维度、不同期间的判定语用逗号拼成一句；"
     "要说两件事就分成两句，各自挂各自的依据。\n"
-    "- 「核对不了」「未能核对」是系统对核对情况的说明，不是结论：不要把它写进正文当结论，也不要据此下判断。"
+    "- 「核对不了」「未能核对」是系统对核对情况的说明，不是结论：不要把它写进正文当结论，也不要据此下判断。\n"
+    "- 引用判定语时不要再在它前面写一句把它开头重复一遍的引言（「过去 26 周过去 26 周退款率…」「波动基线没有做成："
+    "波动基线没有做成：…」）：要么直接写判定语，要么写一句自己的话再引用。"
 )
 #: 写作目录里没有分析结论时，拼在写作规则后面
 ANALYSIS_NONE_PROMPT = (

backend/app/engine/analysis_scope.py

@@ -225,6 +225,7 @@ def _undecomposed(decomposes: list[dict[str, Any]], catalog: Mapping[str, Any],
         if not snapshots:
             return None, NOTE_NO_QUERY
         known: dict[str, tuple[str, str, str]] = {}     # 这份拆解能对上的列：name_key → (源, 表, 列)
+        bare = False                                    # 目录还没维护（没有任何列说明）：对不上是目录的事，不是数据的事
         for artifact in snapshots:
             try:
                 snapshot = load(str(artifact))
@@ -245,6 +246,7 @@ def _undecomposed(decomposes: list[dict[str, Any]], catalog: Mapping[str, Any],
                 # 目录还没维护（表类型、字段的度量类型都没标）时说清楚是目录没维护，不说成「认不出事实表」——
                 # 后者听着像数据的问题，实际上补一下目录就能列
                 return None, NOTE_NO_FACT if _maintained(tables) else NOTE_NOT_MAINTAINED
+            bare = bare or not any((n.get("columns") or {}) for _, n in facts)
             for table, notes in [*facts, *(r for t, n in facts for r in _related(n, tables))]:
                 for column in (notes.get("columns") or {}):
                     known.setdefault(name_key(str(column)), (source, table, name_key(str(column))))
@@ -253,6 +255,10 @@ def _undecomposed(decomposes: list[dict[str, Any]], catalog: Mapping[str, Any],
         for dim, label in zip(_dims(result), _dim_labels(result)):
             hit = known.get(name_key(dim))
             if hit is None:
+                # 目录一列说明都没有时，「对不上」是目录没维护造成的（单表查询时 _fact_tables 会兜底认出那张表，
+                # 走不到上面 NOTE_NOT_MAINTAINED 那一条），照实说目录没维护，不说成数据对不上
+                if bare or not _maintained(tables):
+                    return None, NOTE_NOT_MAINTAINED
                 return None, f"候选维度核对不了：拆解按的「{label}」对不上数据目录里的列"
             used.add(hit)
     return [label for key, label in pool.items() if key not in used], None

backend/tests/test_analysis_conclusion_formats.py

@@ -369,7 +369,8 @@ def test_a_ratio_with_a_unit_is_not_shown_as_a_percentage():
     result = run_sync(analyze("decompose", "ratio", snaps=[snaps], query="Q5", by=["region"], period="week",
                               base="2026-W41", target="2026-W42", numerator="gmv", denominator="orders",
                               label="客单价"))
-    assert result["table"]["formats"] == {"w_base": CONV_PCT, "w_target": CONV_PCT, "mix": CONV_POINTS,
-                                          "rate": CONV_POINTS, "total": CONV_POINTS}
+    assert result["table"]["formats"] == {"w_base": CONV_PCT, "w_target": CONV_PCT}
     assert "r_base_total" not in result["value_formats"] and "r_target_total" not in result["value_formats"]
+    # 影响也是同一个量纲的变化（元 / 单），不能乘一百说成「个百分点」：raw 1.174 不能显示 +117.4 个百分点
+    assert [k for k in ("delta", "mix_total", "rate_total") if k in result["value_formats"]] == []
     assert result["value_formats"]["mix_share"] == CONV_PCT

backend/tests/test_analysis_scope.py

@@ -204,3 +204,16 @@ async def test_the_report_reads_the_catalog_through_the_run_view(shop):
     assert block["not_decomposed"] == ["渠道", "订单状态", "门店类型", "城市"]
     block = await scope.scope_of(catalog, {"mode": "off"}, load=lambda a: snapshot)
     assert block["not_decomposed"] is None and block["note"] == scope.NOTE_NO_CATALOG
+
+
+def test_an_unmaintained_single_table_catalog_says_so_instead_of_a_column_mismatch():
+    """V15（验收复核）：只读一张表、目录还没维护时，_fact_tables 会兜底认出那张表，于是「对不上数据目录里的列」这条
+    把「目录没维护」说成了数据对不上。目录一列说明都没有时照实说目录没维护。"""
+    from app.engine.analysis_scope import NOTE_NOT_MAINTAINED, _undecomposed
+
+    result = {"op": "decompose", "mode": "additive", "inputs": [{"role": "data", "artifact": "a" * 64}],
+              "params": {"by": ["channel"]}, "table": {"columns": ["channel", "base"], "labels": {"channel": "渠道"}}}
+    sources = {"源": {"tables": {"orders": {}}, "masked": []}}
+    snapshots = {"a" * 64: {"source": "源", "sql": "SELECT channel, SUM(amount) AS amt FROM orders GROUP BY channel",
+                            "columns": ["channel", "amt"]}}
+    assert _undecomposed([result], {}, sources, snapshots.get) == (None, NOTE_NOT_MAINTAINED)