From 9827db8a49fb6e4ace76650454bbe96de595f0e5 Mon Sep 17 00:00:00 2001
From: Brad Stein <Brad.Stein@gmail.com>
Date: Sun, 1 Feb 2026 05:30:34 -0300
Subject: [PATCH] atlasbot: guard metric answers with facts

---
 atlasbot/engine/answerer.py | 25 +++++++++++++++++++++++--
 1 file changed, 23 insertions(+), 2 deletions(-)

diff --git a/atlasbot/engine/answerer.py b/atlasbot/engine/answerer.py
index 9a17843..0c51fbd 100644
--- a/atlasbot/engine/answerer.py
+++ b/atlasbot/engine/answerer.py
@@ -414,8 +414,8 @@ class AnswerEngine:
                         best_line = line
                         break
                 best_line = best_line or metric_facts[0]
-                reply_numbers = set(re.findall(r"\\d+(?:\\.\\d+)?", reply))
-                fact_numbers = set(re.findall(r"\\d+(?:\\.\\d+)?", " ".join(metric_facts)))
+                reply_numbers = set(re.findall(r"\d+(?:\.\d+)?", reply))
+                fact_numbers = set(re.findall(r"\d+(?:\.\d+)?", " ".join(metric_facts)))
                 if not reply_numbers or (fact_numbers and not (reply_numbers & fact_numbers)):
                     reply = f"From the latest snapshot: {best_line}."
 
@@ -447,6 +447,9 @@ class AnswerEngine:
                 if note:
                     reply = f"{reply}\n\n{note}"
 
+            if classify.get("question_type") in {"metric", "diagnostic"} and metric_facts:
+                reply = _metric_fact_guard(reply, metric_facts, keyword_tokens)
+
             scores = await self._score_answer(normalized, reply, plan, call_llm)
             claims = await self._extract_claims(normalized, reply, summary, call_llm)
         except LLMLimitReached:
@@ -898,6 +901,24 @@ def _key_fact_lines(lines: list[str], keywords: list[str] | None, limit: int = 6
     return matches
 
 
+def _metric_fact_guard(reply: str, metric_facts: list[str], keywords: list[str]) -> str:
+    if not metric_facts:
+        return reply
+    best_line = None
+    lowered_keywords = [kw.lower() for kw in keywords if kw]
+    for line in metric_facts:
+        line_lower = line.lower()
+        if any(kw in line_lower for kw in lowered_keywords):
+            best_line = line
+            break
+    best_line = best_line or metric_facts[0]
+    reply_numbers = set(re.findall(r"\d+(?:\.\d+)?", reply))
+    fact_numbers = set(re.findall(r"\d+(?:\.\d+)?", " ".join(metric_facts)))
+    if not reply_numbers or (fact_numbers and not (reply_numbers & fact_numbers)):
+        return f"From the latest snapshot: {best_line}."
+    return reply
+
+
 def _lexicon_context(summary: dict[str, Any]) -> str:
     if not isinstance(summary, dict):
         return ""