atlasbot: enforce runbook paths and tighten focus

atlasbot/engine/answerer.py

@@ -340,6 +340,28 @@ class AnswerEngine:
                     model=plan.model,
                     tag="evidence_fix",
                 )
+                if runbook_paths and resolved_runbook and _needs_runbook_reference(normalized, runbook_paths, reply):
+                    if observer:
+                        observer("runbook_enforce", "enforcing runbook path")
+                    enforce_prompt = prompts.RUNBOOK_ENFORCE_PROMPT.format(path=resolved_runbook)
+                    reply = await call_llm(
+                        prompts.RUNBOOK_ENFORCE_SYSTEM,
+                        enforce_prompt + "\nAnswer: " + reply,
+                        context=context,
+                        model=plan.model,
+                        tag="runbook_enforce",
+                    )
+
+            if _needs_focus_fix(normalized, reply, classify):
+                if observer:
+                    observer("focus_fix", "tightening answer")
+                reply = await call_llm(
+                    prompts.EVIDENCE_FIX_SYSTEM,
+                    prompts.FOCUS_FIX_PROMPT + "\nQuestion: " + normalized + "\nDraft: " + reply,
+                    context=context,
+                    model=plan.model,
+                    tag="focus_fix",
+                )
 
             if plan.use_critic:
                 if observer:
@@ -877,6 +899,18 @@ def _needs_evidence_fix(reply: str, classify: dict[str, Any]) -> bool:
     return False
 
 
+def _needs_focus_fix(question: str, reply: str, classify: dict[str, Any]) -> bool:
+    if not reply:
+        return False
+    q_lower = (question or "").lower()
+    if classify.get("question_type") not in {"metric", "diagnostic"} and not re.search(r"\b(how many|list|count)\b", q_lower):
+        return False
+    if reply.count(".") <= 1:
+        return False
+    extra_markers = ("for more", "if you need", "additional", "based on")
+    return any(marker in reply.lower() for marker in extra_markers)
+
+
 def _extract_keywords(normalized: str, sub_questions: list[str], keywords: list[Any] | None) -> list[str]:
     stopwords = {
         "the",

atlasbot/llm/prompts.py

@@ -101,7 +101,20 @@ EVIDENCE_FIX_PROMPT = (
     "rewrite the answer to include those values. "
     "If data is truly missing, keep the draft concise and honest. "
     "If AllowedRunbooks are provided, use an exact path from that list when answering "
-    "documentation or checklist questions and do not invent new paths."
+    "documentation or checklist questions and do not invent new paths. "
+    "If ResolvedRunbook is provided, you must include that exact path and must not say it is missing."
+)
+
+RUNBOOK_ENFORCE_SYSTEM = (
+    CLUSTER_SYSTEM
+    + " Ensure the answer includes the required runbook path. "
+    + "Return a corrected answer only."
+)
+
+RUNBOOK_ENFORCE_PROMPT = (
+    "Rewrite the answer so it explicitly cites the required runbook path. "
+    "If the answer already includes it, keep it. "
+    "Required path: {path}."
 )
 
 RUNBOOK_SELECT_SYSTEM = (
@@ -130,6 +143,11 @@ CRITIC_PROMPT = (
     "Return JSON with fields: issues (list), missing_data (list), risky_claims (list)."
 )
 
+FOCUS_FIX_PROMPT = (
+    "Rewrite the answer to be concise and directly answer the question. "
+    "Remove tangential details and speculative statements."
+)
+
 REVISION_SYSTEM = (
     CLUSTER_SYSTEM
     + " Revise the answer based on critique. "