From 70c7712b603aac78e35bd582e3e75e51ebb70a0b Mon Sep 17 00:00:00 2001
From: Brad Stein <Brad.Stein@gmail.com>
Date: Wed, 4 Feb 2026 13:57:58 -0300
Subject: [PATCH] atlasbot: rank metric fallback lines

---
 atlasbot/engine/answerer.py | 27 +++++++++++++++++++++------
 1 file changed, 21 insertions(+), 6 deletions(-)

diff --git a/atlasbot/engine/answerer.py b/atlasbot/engine/answerer.py
index 6610b5c..ffb6d0d 100644
--- a/atlasbot/engine/answerer.py
+++ b/atlasbot/engine/answerer.py
@@ -21,6 +21,7 @@ log = logging.getLogger(__name__)
 
 FOLLOWUP_SHORT_WORDS = 6
 TOKEN_MIN_LEN = 3
+GENERIC_METRIC_TOKENS = {"atlas", "cluster", "kubernetes", "k8s", "titan", "lab"}
 NS_ENTRY_MIN_LEN = 2
 DEDUP_MIN_SENTENCES = 3
 RUNBOOK_SIMILARITY_THRESHOLD = 0.4
@@ -371,11 +372,9 @@ class AnswerEngine:
                             max_lines=min(2, max(1, plan.max_subquestions)),
                         )
                         if not global_metric_facts and (keyword_tokens or question_tokens):
-                            global_metric_facts = _filter_lines_by_keywords(
-                                global_facts,
-                                keyword_tokens or question_tokens,
-                                max_lines=2,
-                            )
+                            tokens = set(keyword_tokens or question_tokens)
+                            tokens = {tok for tok in tokens if tok and tok not in GENERIC_METRIC_TOKENS}
+                            global_metric_facts = _rank_metric_lines(global_facts, tokens, max_lines=2)
                         if global_metric_facts:
                             key_facts = _merge_fact_lines(global_metric_facts, key_facts)
                     all_tokens = _merge_tokens(signal_tokens, keyword_tokens, question_tokens)
@@ -434,7 +433,8 @@ class AnswerEngine:
                     if not metric_facts:
                         if observer:
                             observer("retrieve", "fallback metric selection")
-                        fallback_candidates = _filter_lines_by_keywords(summary_lines, all_tokens, max_lines=200)
+                        token_set = {tok for tok in all_tokens if tok and tok not in GENERIC_METRIC_TOKENS}
+                        fallback_candidates = _rank_metric_lines(summary_lines, token_set, max_lines=200)
                         if fallback_candidates:
                             metric_facts = await _select_fact_lines(
                                 call_llm,
@@ -2018,6 +2018,21 @@ def _filter_lines_by_keywords(lines: list[str], keywords: list[str], max_lines:
     return (filtered or lines)[:max_lines]
 
 
+def _rank_metric_lines(lines: list[str], tokens: set[str], max_lines: int) -> list[str]:
+    if not lines or not tokens:
+        return []
+    ranked: list[tuple[int, int, str]] = []
+    for line in lines:
+        lower = line.lower()
+        hits = sum(1 for tok in tokens if tok in lower)
+        if not hits:
+            continue
+        has_number = 1 if re.search(r"\d", line) else 0
+        ranked.append((has_number, hits, line))
+    ranked.sort(key=lambda item: (-item[0], -item[1], item[2]))
+    return [item[2] for item in ranked[:max_lines]]
+
+
 def _global_facts(lines: list[str]) -> list[str]:
     if not lines:
         return []