报告前面加一段模型写的解读（issue #113 R1）

引擎在同一份 packet 上给出与对话同源卡相同的事实（include_reading_facts），
报告任务交付前用一次结构化模型调用写八节解读，校验不过或失败就不出解读、
报告照常交付。解读存在计算快照里，读接口一起返回，页面放在引擎正文之前，
后面标「计算依据」。用量按实际 token 记账（BUG-1460、BUG-1461）。

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LutgzyJqNhPpZy1nFsJtN3

scripts/professional_report_reference.py

@@ -195,6 +195,18 @@ def _export_args(birth: dict[str, Any]) -> SimpleNamespace:
     return SimpleNamespace(**payload)
 
 
+def _reading_facts(packet: dict, full_reading: dict, minute_confirmed: bool, today: str | None) -> dict[str, Any]:
+    """Facts for the model-written reading (issue #113 R1). Never fails the report."""
+    try:
+        try:
+            from scripts.report_render.reading_facts import build_report_reading_facts
+        except ModuleNotFoundError:  # pragma: no cover - direct scripts/ execution path
+            from report_render.reading_facts import build_report_reading_facts
+        return build_report_reading_facts(packet, full_reading, minute_confirmed=minute_confirmed, today=today)
+    except Exception as exc:  # noqa: BLE001 - the reading is optional, the report is not
+        return {"schema": "report-reading-facts-v1", "gaps": ["reading_facts_unavailable"], "error_type": type(exc).__name__}
+
+
 def _load_report_cache():
     try:
         from scripts import consult_full_data_cache as cache
@@ -215,6 +227,7 @@ def _report_cache_identity(
     languages: list[str],
     include_fact_tables: bool,
     sha: str,
+    reading: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
     return {
         "birth": birth,
@@ -225,6 +238,8 @@ def _report_cache_identity(
         "include_fact_tables": include_fact_tables,
         "report_version": REPORT_VERSION_FULL,
         "github_sha": sha,
+        "include_reading_facts": reading is not None,
+        **({"reading": reading} if reading is not None else {}),
     }
 
 
@@ -237,6 +252,7 @@ def _assemble_professional_report_reference(
     languages: list[str],
     include_fact_tables: bool,
     engine,
+    reading: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
     full_reading = handler._compute_full_reading_for_thematic(birth)
     resolved_engine = engine or _load_engine()
@@ -270,6 +286,9 @@ def _assemble_professional_report_reference(
                 "reader_dasha_applicability": clean_reader_appendix_markdown(render_dasha_applicability(packet))}
                if include_fact_tables else {}),
             **(english if edition == FULL_DATA_EDITION and "en" in languages else {}),
+            **({"reading_facts": _reading_facts(
+                packet, full_reading, reading["minute_confirmed"], reading.get("today"),
+            )} if reading is not None and edition == FULL_DATA_EDITION else {}),
         }
     return {
         "format": "json",
@@ -278,6 +297,21 @@ def _assemble_professional_report_reference(
     }
 
 
+def _reading_request(body: dict[str, Any]) -> dict[str, Any] | None:
+    """`include_reading_facts: true` asks for the reading facts; off by default."""
+    if body.get("include_reading_facts") is not True:
+        return None
+    try:
+        from scripts.consult_card_domain_facts import minute_confirmed_from_body
+    except ModuleNotFoundError:  # pragma: no cover - direct scripts/ execution path
+        from consult_card_domain_facts import minute_confirmed_from_body
+    today = body.get("today")
+    return {
+        "minute_confirmed": minute_confirmed_from_body(body),
+        "today": today if isinstance(today, str) else None,
+    }
+
+
 def build_professional_report_reference(handler, body: dict[str, Any], *, engine=None) -> dict[str, Any]:
     """Build one JSON or Markdown response from one reused full-reading result."""
     if not isinstance(body, dict):
@@ -291,6 +325,7 @@ def build_professional_report_reference(handler, body: dict[str, Any], *, engine
 
     birth = handler._high_rigor_birth_payload(body)
     include_fact_tables = body.get("include_fact_tables") is True
+    reading = _reading_request(body) if edition == FULL_DATA_EDITION and output_format == "markdown" else None
     sha = _report_cache_sha()
     use_cache = (
         report_reference_cache_enabled()
@@ -300,16 +335,16 @@ def build_professional_report_reference(handler, body: dict[str, Any], *, engine
     )
     if not use_cache:
         return _assemble_professional_report_reference(
-            handler, birth, output_format, edition, packs, languages, include_fact_tables, engine,
+            handler, birth, output_format, edition, packs, languages, include_fact_tables, engine, reading,
         )
     identity = _report_cache_identity(
-        birth, output_format, edition, packs, languages, include_fact_tables, sha,
+        birth, output_format, edition, packs, languages, include_fact_tables, sha, reading,
     )
     started = time.perf_counter()
 
     def builder(_identity: dict[str, Any]) -> dict[str, Any]:
         return _assemble_professional_report_reference(
-            handler, birth, output_format, edition, packs, languages, include_fact_tables, engine,
+            handler, birth, output_format, edition, packs, languages, include_fact_tables, engine, reading,
         )
 
     cached = _load_report_cache().get_or_build(