diff --git a/docs/FIX_CONTEXTUAL_REENTRY_BEFORE_TERMINAL_WORKFLOW_RESUME_20260922.md b/docs/FIX_CONTEXTUAL_REENTRY_BEFORE_TERMINAL_WORKFLOW_RESUME_20260922.md
new file mode 100644
index 00000000..0cdbfe93
--- /dev/null
+++ b/docs/FIX_CONTEXTUAL_REENTRY_BEFORE_TERMINAL_WORKFLOW_RESUME_20260922.md
@@ -0,0 +1,65 @@
+# Fix: contextual reentry before terminal workflow resume
+
+## Problem
+
+A paused workflow with a declarative `expected_input.semantic_classifier` could receive a
+compound reply such as:
+
+```text
+ainda nao. Eu nao contratei esse neymar jr
+```
+
+If the classifier returned only `NAO`, the framework immediately resumed the paused workflow.
+A backend workflow was then free to enter a terminal branch (for example human handoff) before
+the substantive remainder of the same user turn was reinterpreted by normal routing.
+
+This is an orchestration problem in the framework, not a domain rule for billing and not a
+frontend problem.
+
+## Corrected precedence
+
+Literal `expected_input` matches keep absolute precedence and are unchanged. For non-literal
+semantic matches, when the workflow itself declares an option with
+`option_actions.<option>.action: contextual_reentry`, the framework now performs one generic
+precedence validation before committing to a normal workflow resume.
+
+The validation asks only whether the current utterance is completely consumed by the selected
+resume option or whether it also contains substantive information that still needs interpretation.
+It contains no domain vocabulary and no hardcoded `SIM`/`NAO` business meaning.
+
+The effective order is now:
+
+1. deterministic `expected_input` exact match;
+2. explicit global human-handoff control;
+3. workflow `semantic_classifier`;
+4. if the semantic result would resume and the contract declares `contextual_reentry`, validate
+   whether substantive remainder exists;
+5. substantive remainder -> `contextual_reentry` and normal routing;
+6. pure reply -> resume paused workflow normally;
+7. only after a genuine resume can the backend workflow reach its own terminal/handoff branch.
+
+A workflow can explicitly disable this safeguard with:
+
+```yaml
+semantic_classifier:
+  contextual_reentry_precedence: false
+```
+
+The default is enabled whenever a `contextual_reentry` option is declared.
+
+## Observability
+
+When reentry preempts a semantic resume, route metadata now includes:
+
+- `contextual_reentry_preempted_resume: true`
+- `initial_classifier_output`
+- `contextual_reentry_precedence_raw_output`
+- the existing contextual-reentry metadata (`original_input`, `classifier_output`, bounded context)
+
+## Regression tests
+
+Tests cover both directions:
+
+- a compound negative reply whose first classifier result is `NAO` is protected from premature
+  resume and is rerouted through contextual reentry;
+- a pure semantic negative reply remains a normal workflow resume.
diff --git a/libs/agent_framework/build/lib/agent_framework/routing/enterprise_router.py b/libs/agent_framework/build/lib/agent_framework/routing/enterprise_router.py
index bfb476a9..1a08d895 100644
--- a/libs/agent_framework/build/lib/agent_framework/routing/enterprise_router.py
+++ b/libs/agent_framework/build/lib/agent_framework/routing/enterprise_router.py
@@ -256,6 +256,79 @@ class EnterpriseRouter:
                     return matched, raw
         return None, raw
 
+    async def _prefer_contextual_reentry_over_semantic_resume(
+        self,
+        *,
+        text: str,
+        classified: str,
+        expected_input: dict[str, Any],
+        pause_prompt: str,
+        relevant_conversation_context: str,
+    ) -> tuple[bool, str | None, str | None]:
+        """Protect contextual reentry from a premature workflow resume.
+
+        ``semantic_classifier`` is agent-declared and normally authoritative. A
+        special ambiguity exists when the same contract declares an option whose
+        action is ``contextual_reentry``: an LLM can correctly notice a leading
+        answer to the pause (for example a negative acknowledgement) but miss the
+        substantive remainder of the same utterance. Resuming the workflow in
+        that situation can immediately reach a terminal branch such as handoff,
+        before normal routing sees the new information.
+
+        The framework therefore performs a generic *precedence validation* only
+        for non-literal semantic matches and only when the contract explicitly
+        declares contextual reentry. No domain vocabulary or SIM/NAO semantics
+        are embedded here.
+        """
+        if self.llm is None or not isinstance(expected_input, dict):
+            return False, None, None
+        classifier = expected_input.get("semantic_classifier")
+        if not isinstance(classifier, dict):
+            return False, None, None
+        option_actions = classifier.get("option_actions")
+        if not isinstance(option_actions, dict):
+            return False, None, None
+
+        reentry_option = None
+        for option, cfg in option_actions.items():
+            if isinstance(cfg, dict) and str(cfg.get("action") or "").strip().lower() == "contextual_reentry":
+                reentry_option = str(option)
+                break
+        if not reentry_option or str(classified).upper() == reentry_option.upper():
+            return False, reentry_option, None
+        if classifier.get("contextual_reentry_precedence") is False:
+            return False, reentry_option, None
+
+        prompt = (
+            "Você valida precedência entre retomar um workflow pausado e fazer reentrada contextual. "
+            "Não decida a intenção de negócio. Analise apenas se a mensagem atual é totalmente "
+            "consumida pela opção já classificada ou se contém informação substantiva adicional que "
+            "precisa ser interpretada pelo pipeline normal.\n\n"
+            f"Pergunta pendente: {str(pause_prompt or '').strip()}\n"
+            f"Opção inicialmente classificada: {str(classified)}\n"
+            f"Contexto relevante: {str(relevant_conversation_context or '').strip()}\n"
+            f"Mensagem atual: {str(text or '').strip()}\n\n"
+            "Responda somente REENTER se houver pedido, objeção, correção, explicação, motivo, entidade, "
+            "valor, referência ou outro fato novo que ainda precise de interpretação além da resposta "
+            "à pergunta pendente. Responda somente RESUME se a mensagem inteira for apenas a resposta "
+            "à pergunta pendente, admitindo somente cortesia sem nova demanda."
+        )
+        try:
+            answer = await self.llm.ainvoke(
+                [
+                    {"role": "system", "content": prompt},
+                    {"role": "user", "content": str(text or "")},
+                ],
+                profile_name="router",
+                component_name="workflow.expected_input.precedence",
+                generation_name="workflow.expected_input.contextual_reentry_precedence",
+            )
+        except Exception as exc:
+            logger.warning("Falha ao validar precedência de contextual_reentry: %s", exc)
+            return False, reentry_option, None
+        raw = str(answer or "").strip()
+        return raw.upper() == "REENTER", reentry_option, raw
+
     @staticmethod
     def _last_assistant_prompt(state: dict[str, Any], current_text: str) -> str:
         history = [item for item in (state.get("history") or []) if isinstance(item, dict)]
@@ -524,6 +597,39 @@ class EnterpriseRouter:
                         option_actions = option_actions if isinstance(option_actions, dict) else {}
                         action_cfg = option_actions.get(str(classified)) or option_actions.get(str(classified).upper())
                         action_cfg = action_cfg if isinstance(action_cfg, dict) else {}
+
+                        # A semantic match that would resume the paused workflow
+                        # must not prematurely win over an explicitly declared
+                        # contextual_reentry option when the same utterance also
+                        # carries substantive new information. This validation is
+                        # intentionally generic and runs only after literal
+                        # expected_input matching has already failed.
+                        if str(action_cfg.get("action") or "").strip().lower() != "contextual_reentry":
+                            prefer_reentry, reentry_option, precedence_raw = await self._prefer_contextual_reentry_over_semantic_resume(
+                                text=str(text),
+                                classified=str(classified),
+                                expected_input=expected_input,
+                                pause_prompt=str(pause.get("prompt") or ""),
+                                relevant_conversation_context=relevant_context,
+                            )
+                            if prefer_reentry and reentry_option:
+                                decision = await self._route_contextual_reentry(
+                                    state=state,
+                                    original_input=str(text),
+                                    relevant_context=relevant_context,
+                                    classifier_output=str(reentry_option),
+                                    raw_classifier=raw_classifier,
+                                    allowed_values=list(expected_input.get("allowed_values") or []),
+                                )
+                                decision.metadata = {
+                                    **dict(decision.metadata or {}),
+                                    "contextual_reentry_preempted_resume": True,
+                                    "initial_classifier_output": str(classified),
+                                    "contextual_reentry_precedence_raw_output": precedence_raw,
+                                }
+                                await self._emit(decision, state)
+                                return decision
+
                         if str(action_cfg.get("action") or "").strip().lower() == "contextual_reentry":
                             decision = await self._route_contextual_reentry(
                                 state=state,
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diff --git a/libs/agent_framework/src/agent_framework/routing/enterprise_router.py b/libs/agent_framework/src/agent_framework/routing/enterprise_router.py
index bfb476a9..1a08d895 100644
--- a/libs/agent_framework/src/agent_framework/routing/enterprise_router.py
+++ b/libs/agent_framework/src/agent_framework/routing/enterprise_router.py
@@ -256,6 +256,79 @@ class EnterpriseRouter:
                     return matched, raw
         return None, raw
 
+    async def _prefer_contextual_reentry_over_semantic_resume(
+        self,
+        *,
+        text: str,
+        classified: str,
+        expected_input: dict[str, Any],
+        pause_prompt: str,
+        relevant_conversation_context: str,
+    ) -> tuple[bool, str | None, str | None]:
+        """Protect contextual reentry from a premature workflow resume.
+
+        ``semantic_classifier`` is agent-declared and normally authoritative. A
+        special ambiguity exists when the same contract declares an option whose
+        action is ``contextual_reentry``: an LLM can correctly notice a leading
+        answer to the pause (for example a negative acknowledgement) but miss the
+        substantive remainder of the same utterance. Resuming the workflow in
+        that situation can immediately reach a terminal branch such as handoff,
+        before normal routing sees the new information.
+
+        The framework therefore performs a generic *precedence validation* only
+        for non-literal semantic matches and only when the contract explicitly
+        declares contextual reentry. No domain vocabulary or SIM/NAO semantics
+        are embedded here.
+        """
+        if self.llm is None or not isinstance(expected_input, dict):
+            return False, None, None
+        classifier = expected_input.get("semantic_classifier")
+        if not isinstance(classifier, dict):
+            return False, None, None
+        option_actions = classifier.get("option_actions")
+        if not isinstance(option_actions, dict):
+            return False, None, None
+
+        reentry_option = None
+        for option, cfg in option_actions.items():
+            if isinstance(cfg, dict) and str(cfg.get("action") or "").strip().lower() == "contextual_reentry":
+                reentry_option = str(option)
+                break
+        if not reentry_option or str(classified).upper() == reentry_option.upper():
+            return False, reentry_option, None
+        if classifier.get("contextual_reentry_precedence") is False:
+            return False, reentry_option, None
+
+        prompt = (
+            "Você valida precedência entre retomar um workflow pausado e fazer reentrada contextual. "
+            "Não decida a intenção de negócio. Analise apenas se a mensagem atual é totalmente "
+            "consumida pela opção já classificada ou se contém informação substantiva adicional que "
+            "precisa ser interpretada pelo pipeline normal.\n\n"
+            f"Pergunta pendente: {str(pause_prompt or '').strip()}\n"
+            f"Opção inicialmente classificada: {str(classified)}\n"
+            f"Contexto relevante: {str(relevant_conversation_context or '').strip()}\n"
+            f"Mensagem atual: {str(text or '').strip()}\n\n"
+            "Responda somente REENTER se houver pedido, objeção, correção, explicação, motivo, entidade, "
+            "valor, referência ou outro fato novo que ainda precise de interpretação além da resposta "
+            "à pergunta pendente. Responda somente RESUME se a mensagem inteira for apenas a resposta "
+            "à pergunta pendente, admitindo somente cortesia sem nova demanda."
+        )
+        try:
+            answer = await self.llm.ainvoke(
+                [
+                    {"role": "system", "content": prompt},
+                    {"role": "user", "content": str(text or "")},
+                ],
+                profile_name="router",
+                component_name="workflow.expected_input.precedence",
+                generation_name="workflow.expected_input.contextual_reentry_precedence",
+            )
+        except Exception as exc:
+            logger.warning("Falha ao validar precedência de contextual_reentry: %s", exc)
+            return False, reentry_option, None
+        raw = str(answer or "").strip()
+        return raw.upper() == "REENTER", reentry_option, raw
+
     @staticmethod
     def _last_assistant_prompt(state: dict[str, Any], current_text: str) -> str:
         history = [item for item in (state.get("history") or []) if isinstance(item, dict)]
@@ -524,6 +597,39 @@ class EnterpriseRouter:
                         option_actions = option_actions if isinstance(option_actions, dict) else {}
                         action_cfg = option_actions.get(str(classified)) or option_actions.get(str(classified).upper())
                         action_cfg = action_cfg if isinstance(action_cfg, dict) else {}
+
+                        # A semantic match that would resume the paused workflow
+                        # must not prematurely win over an explicitly declared
+                        # contextual_reentry option when the same utterance also
+                        # carries substantive new information. This validation is
+                        # intentionally generic and runs only after literal
+                        # expected_input matching has already failed.
+                        if str(action_cfg.get("action") or "").strip().lower() != "contextual_reentry":
+                            prefer_reentry, reentry_option, precedence_raw = await self._prefer_contextual_reentry_over_semantic_resume(
+                                text=str(text),
+                                classified=str(classified),
+                                expected_input=expected_input,
+                                pause_prompt=str(pause.get("prompt") or ""),
+                                relevant_conversation_context=relevant_context,
+                            )
+                            if prefer_reentry and reentry_option:
+                                decision = await self._route_contextual_reentry(
+                                    state=state,
+                                    original_input=str(text),
+                                    relevant_context=relevant_context,
+                                    classifier_output=str(reentry_option),
+                                    raw_classifier=raw_classifier,
+                                    allowed_values=list(expected_input.get("allowed_values") or []),
+                                )
+                                decision.metadata = {
+                                    **dict(decision.metadata or {}),
+                                    "contextual_reentry_preempted_resume": True,
+                                    "initial_classifier_output": str(classified),
+                                    "contextual_reentry_precedence_raw_output": precedence_raw,
+                                }
+                                await self._emit(decision, state)
+                                return decision
+
                         if str(action_cfg.get("action") or "").strip().lower() == "contextual_reentry":
                             decision = await self._route_contextual_reentry(
                                 state=state,
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Binary files a/tests/__pycache__/test_transaction_state_router_interruption.cpython-313-pytest-9.0.2.pyc and b/tests/__pycache__/test_transaction_state_router_interruption.cpython-313-pytest-9.0.2.pyc differ
diff --git a/tests/test_expected_input_semantic_classifier.py b/tests/test_expected_input_semantic_classifier.py
index b2c09766..e0afb5ad 100644
--- a/tests/test_expected_input_semantic_classifier.py
+++ b/tests/test_expected_input_semantic_classifier.py
@@ -300,3 +300,81 @@ def test_invoice_explanation_uses_continue_as_contextual_reentry_option():
     assert "quatorze e noventa e nove" in prompt and "CONTINUAR" in prompt
     assert "Nunca trate" in prompt
     assert "OUTRO" in prompt
+
+@pytest.mark.asyncio
+async def test_contextual_reentry_precedence_prevents_premature_resume_and_terminal_handoff(tmp_path):
+    routing = tmp_path / "routing.yaml"
+    routing.write_text(
+        """
+router:
+  fallback_agent: fallback_agent
+  confidence_threshold: 0.70
+intents:
+  - name: contestation
+    agent: contestation_agent
+    description: contestar cobrança não reconhecida
+    domain: demo
+    keywords: [contestar]
+    mcp_tools: [contestar_cobranca]
+""",
+        encoding="utf-8",
+    )
+    # 1) classifier misses the remainder and returns NAO;
+    # 2) generic precedence validator detects substantive remainder;
+    # 3) contextual reentry routes the full turn normally.
+    llm = _ClassifierLLM([
+        "NAO",
+        "REENTER",
+        '{"intent":"contestation","agent":"contestation_agent","confidence":0.99,"reason":"há contestação de cobrança não reconhecida"}',
+    ])
+    settings = SimpleNamespace(
+        ROUTING_CONFIG_PATH=str(routing),
+        ENABLE_LLM_ROUTER=True,
+        ENABLE_ROUTE_STICKINESS=False,
+    )
+    router = EnterpriseRouter(settings, llm=llm)
+    state = _state(
+        "ainda nao. Eu nao contratei esse neymar jr",
+        ["SIM", "NAO", "CONTINUAR"],
+        "Classifique {{ user_input }} considerando {{ relevant_conversation_context }} em {{ allowed_values }}",
+        history=[
+            {"role": "user", "content": "estou achando que minha fatura esta errada", "metadata": {"message_id": "anchor"}},
+            {"role": "assistant", "content": "Expliquei as cobranças. Com essa explicação, sanei sua dúvida?", "metadata": {"intent": "owner_intent"}},
+            {"role": "user", "content": "ainda nao. Eu nao contratei esse neymar jr", "metadata": {}},
+        ],
+        include_relevant_context=True,
+    )
+    state["pending_domain_workflow"]["context_anchor_message_id"] = "anchor"
+    state["pending_domain_workflow"]["pause"]["expected_input"]["semantic_classifier"]["option_actions"] = {
+        "CONTINUAR": {"action": "contextual_reentry"}
+    }
+
+    decision = await router.route(state)
+
+    assert decision.intent == "contestation"
+    assert decision.agent == "contestation_agent"
+    assert decision.metadata["contextual_reentry"] is True
+    assert decision.metadata["contextual_reentry_preempted_resume"] is True
+    assert decision.metadata["initial_classifier_output"] == "NAO"
+    assert decision.metadata["classifier_output"] == "CONTINUAR"
+    assert decision.metadata["contextual_reentry_precedence_raw_output"] == "REENTER"
+    assert not decision.metadata.get("workflow_resume")
+
+
+@pytest.mark.asyncio
+async def test_contextual_reentry_precedence_keeps_pure_semantic_resume(tmp_path):
+    router = _router(tmp_path, ["NAO", "RESUME"])
+    state = _state(
+        "ainda não resolveu",
+        ["SIM", "NAO", "CONTINUAR"],
+        "Classifique {{ user_input }} em {{ allowed_values }}",
+    )
+    state["pending_domain_workflow"]["pause"]["expected_input"]["semantic_classifier"]["option_actions"] = {
+        "CONTINUAR": {"action": "contextual_reentry"}
+    }
+
+    decision = await router.route(state)
+
+    assert decision.metadata["workflow_resume"] is True
+    assert decision.metadata["normalized_input"] == "NAO"
+    assert not decision.metadata.get("contextual_reentry")