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diff --git a/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/agent_runtime.py b/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/agent_runtime.py
index aeaabec..96deab0 100644
--- a/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/agent_runtime.py
+++ b/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/agent_runtime.py
@@ -1497,6 +1497,80 @@ class AgentRuntimeMixin:
         newest = list(reversed(blocks))
         return "\n".join(f"history:{i+1}: {block}" for i, block in enumerate(newest))
 
+    @staticmethod
+    def _transaction_context_priority_view(context: Any) -> str:
+        """Group bounded history by reconciliation priority without losing recency.
+
+        The temporal reconciler is a fallback, so current-turn values and validated
+        transaction state are supplied separately.  Within historical conversation,
+        assistant explanations are intentionally considered before older user turns:
+        they frequently carry grounded relationships produced from tool/evidence
+        results (for example item -> amount).  They remain interpretive candidates
+        only and must still pass the configured authoritative pre-validation.
+        """
+        ordered = AgentRuntimeMixin._transaction_context_newest_first(context)
+        if not ordered:
+            return ""
+        assistant: list[str] = []
+        user: list[str] = []
+        other: list[str] = []
+        for line in ordered.splitlines():
+            payload = line.split(": ", 1)[1] if ": " in line else line
+            low = payload.lower().lstrip()
+            if low.startswith(("assistant:", "agente:")):
+                assistant.append(line)
+            elif low.startswith(("user:", "cliente:")):
+                user.append(line)
+            else:
+                other.append(line)
+
+        sections: list[str] = []
+        if assistant:
+            sections.append(
+                "priority_3_previous_assistant_tool_or_evidence_context:\n" + "\n".join(assistant)
+            )
+        if user:
+            sections.append("priority_4_previous_user_utterances:\n" + "\n".join(user))
+        if other:
+            sections.append("priority_5_other_conversational_context:\n" + "\n".join(other))
+        return "\n".join(sections)
+
+    @staticmethod
+    def _apply_transaction_reconciliation(
+        arguments: dict[str, Any],
+        reconciliation: dict[str, Any] | None,
+        *,
+        locked_current_fields: set[str] | None = None,
+    ) -> tuple[dict[str, Any], list[str], list[str]]:
+        """Apply temporal reconciliation without mutating explicit current-turn fields.
+
+        Values extracted from the current user utterance have highest precedence for
+        that turn.  The temporal reconciler may use them as anchors, but it cannot
+        clear or overwrite them.  A later authoritative pre-validation step may
+        still reject a current value and trigger the dedicated recovery path.
+        """
+        out = dict(arguments or {})
+        rec = dict(reconciliation or {})
+        locked = {str(name) for name in (locked_current_fields or set())}
+        ignored_clears: list[str] = []
+        ignored_values: list[str] = []
+
+        for field in rec.get("clear_fields") or []:
+            name = str(field)
+            if name in locked:
+                ignored_clears.append(name)
+                continue
+            out.pop(name, None)
+
+        for field, value in dict(rec.get("values") or {}).items():
+            name = str(field)
+            if name in locked:
+                ignored_values.append(name)
+                continue
+            out[name] = value
+
+        return out, ignored_clears, ignored_values
+
     async def _reconcile_transaction_parameters(
         self,
         state: dict[str, Any],
@@ -1543,7 +1617,7 @@ class AgentRuntimeMixin:
             suffix = "\n\nCONTINUAÇÃO ATUAL DO CLIENTE:\n"
             if prefix in effective and suffix in effective:
                 conversational_context = effective.split(prefix, 1)[1].split(suffix, 1)[0].strip()
-        ordered_context = self._transaction_context_newest_first(conversational_context)
+        ordered_context = self._transaction_context_priority_view(conversational_context)
         cached = route_meta.get("transaction_parameter_values")
         effective_known = dict(known_arguments or {})
         if isinstance(cached, dict):
@@ -3038,15 +3112,22 @@ class AgentRuntimeMixin:
                         parameter_names=required_fields,
                         known_arguments=arguments,
                     )
-                    for field in reconciliation.get("clear_fields") or []:
-                        arguments.pop(str(field), None)
-                    arguments.update(dict(reconciliation.get("values") or {}))
+                    locked_current_fields = {
+                        str(k) for k, v in dict(extracted_current or {}).items() if v not in _EMPTY_VALUES
+                    }
+                    arguments, ignored_clears, ignored_values = self._apply_transaction_reconciliation(
+                        arguments, reconciliation, locked_current_fields=locked_current_fields
+                    )
                     state["transaction_parameter_reconciliation"] = {
                         "tool_name": tool_name,
                         "trigger": "traditional_collection_unresolved",
                         "decisions": dict(reconciliation.get("decisions") or {}),
                         "provenance": dict(reconciliation.get("provenance") or {}),
                         "clear_fields": list(reconciliation.get("clear_fields") or []),
+                        "values": dict(reconciliation.get("values") or {}),
+                        "locked_current_fields": sorted(locked_current_fields),
+                        "ignored_clear_fields": sorted(ignored_clears),
+                        "ignored_reconciled_values": sorted(ignored_values),
                     }
                 else:
                     state.pop("transaction_parameter_reconciliation", None)
@@ -3321,21 +3402,52 @@ class AgentRuntimeMixin:
         policy = self._resolve_tool_execution_policy(selected_action, action_args)
         required = [str(name) for name in (policy.get("requires") or [])]
 
-        # Valores já estruturados no contexto podem satisfazer requirements sem
-        # parsing textual. Para qualquer required field ainda ausente, a fala do
-        # usuário é interpretada exclusivamente pelo extrator LLM transacional.
+        # Primeiro turno transacional segue a mesma regra de COLLECTING_PARAMETERS:
+        # 1) coleta tradicional SOMENTE da fala atual; 2) reconciliação temporal
+        # apenas como fallback se ainda houver required fields faltando.
+        # Isso evita que histórico altere o happy path e, ao mesmo tempo, permite
+        # resolver referências contextuais quando a fala atual é incompleta.
         missing_initial = self._missing_required_arguments(policy, action_args)
-        # No primeiro turno, a fala atual pode fornecer/corrigir qualquer required
-        # field, inclusive um valor que exista no contexto estruturado mas pertença
-        # a uma transação anterior. O extrator continua restrito ao contrato
-        # ``requires`` e só sobrescreve quando a LLM realmente extrai um valor.
-        extracted_initial = await self._extract_transaction_parameters(
+        extracted_initial = await self._extract_transaction_parameters_current_only(
             state,
             tool_name=selected_action,
             missing_parameters=required,
             known_arguments={k: v for k, v in action_args.items() if k not in set(required)},
         )
         action_args.update(extracted_initial)
+        state["transaction_parameter_collection"] = {
+            "tool_name": selected_action,
+            "mode": "current_turn",
+            "resolved_fields": sorted(str(k) for k in (extracted_initial or {}).keys()),
+        }
+
+        missing_after_current = self._missing_required_arguments(policy, action_args)
+        if missing_after_current:
+            reconciliation = await self._reconcile_transaction_parameters(
+                state,
+                tool_name=selected_action,
+                parameter_names=required,
+                known_arguments=action_args,
+            )
+            locked_current_fields = {
+                str(k) for k, v in dict(extracted_initial or {}).items() if v not in _EMPTY_VALUES
+            }
+            action_args, ignored_clears, ignored_values = self._apply_transaction_reconciliation(
+                action_args, reconciliation, locked_current_fields=locked_current_fields
+            )
+            state["transaction_parameter_reconciliation"] = {
+                "tool_name": selected_action,
+                "trigger": "initial_traditional_collection_unresolved",
+                "decisions": dict(reconciliation.get("decisions") or {}),
+                "provenance": dict(reconciliation.get("provenance") or {}),
+                "clear_fields": list(reconciliation.get("clear_fields") or []),
+                "values": dict(reconciliation.get("values") or {}),
+                "locked_current_fields": sorted(locked_current_fields),
+                "ignored_clear_fields": sorted(ignored_clears),
+                "ignored_reconciled_values": sorted(ignored_values),
+            }
+        else:
+            state.pop("transaction_parameter_reconciliation", None)
 
         # O mapper MCP continua responsável somente por parâmetros auxiliares que
         # não pertencem ao contrato transacional.
diff --git a/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/transaction_parameters.py b/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/transaction_parameters.py
index 88cfbeb..55cc1c3 100644
--- a/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/transaction_parameters.py
+++ b/agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/transaction_parameters.py
@@ -113,33 +113,217 @@ async def reconcile_transaction_parameters(
             for name in names
         }
     }
+
+    def _anchor_tokens(value: Any) -> list[str]:
+        """Return generic textual variants for a known scalar anchor."""
+        if value in _EMPTY_VALUES:
+            return []
+        raw = str(value).strip().lower()
+        tokens = {raw}
+        try:
+            number = float(str(value).replace(",", "."))
+            tokens.add(f"{number:.2f}")
+            tokens.add(f"{number:.2f}".replace(".", ","))
+            if number.is_integer():
+                tokens.add(str(int(number)))
+        except (TypeError, ValueError):
+            pass
+        return [token for token in tokens if token]
+
+    def _anchor_relation_candidates(context: str, arguments: Mapping[str, Any]) -> list[str]:
+        """Surface history fragments related to any already-known parameter.
+
+        This is not a second reconciliation pass and does not resolve anything
+        deterministically.  It only structures the SAME temporal scan so the LLM
+        can use known/current fields as cross-field anchors while reconciling all
+        pending fields coherently in one call.
+        """
+        if not context or not arguments:
+            return []
+        # Keep role/history prefixes but split long assistant explanations into
+        # smaller semantic clauses (bullets/semicolons) so one anchor is not lost
+        # among many unrelated entity/value pairs.
+        fragments: list[str] = []
+        for raw_line in context.splitlines():
+            line = raw_line.strip()
+            if not line:
+                continue
+            parts = [part.strip() for part in re.split(r"\s*\*\s*|\s*;\s*", line) if part.strip()]
+            fragments.extend(parts or [line])
+
+        candidates: list[str] = []
+        for field_name, field_value in arguments.items():
+            variants = _anchor_tokens(field_value)
+            if not variants:
+                continue
+            for fragment in fragments:
+                low = fragment.lower()
+                if any(token in low for token in variants):
+                    candidates.append(f"anchor[{field_name}={field_value}]: {fragment}")
+        return list(dict.fromkeys(candidates))
+
+    def _structured_evidence_blocks(context: str, arguments: Mapping[str, Any]) -> list[dict[str, Any]]:
+        """Represent the same bounded history as explicit message evidence blocks.
+
+        The reconciler remains a single LLM call.  This helper only prevents role,
+        recency and anchor relationships from being hidden inside one prose blob.
+        It is fully domain-neutral: field meaning still comes from parameter_schema.
+        """
+        blocks: list[dict[str, Any]] = []
+        current_role = "other"
+        current_lines: list[str] = []
+        rank = 0
+
+        def flush() -> None:
+            nonlocal rank, current_lines, current_role
+            if not current_lines:
+                return
+            text_block = " ".join(x.strip() for x in current_lines if x.strip()).strip()
+            current_lines = []
+            if not text_block:
+                return
+
+            # A single assistant message often contains a list of independent
+            # entity/attribute relations (for example several invoice items).
+            # Keeping the whole answer as one evidence block makes an otherwise
+            # exact anchor ambiguous because every entity in the list competes
+            # inside the same block.  Segment LOCAL relations while preserving
+            # the original role, priority and message recency.  This is still the
+            # same temporal reconciliation and the same single LLM call.
+            fragments = [
+                frag.strip(" \t-•")
+                for frag in re.split(
+                    r"\s+(?:\*|•)\s+|\s*;\s+|\s+(?=\d+[.)]\s+)",
+                    text_block,
+                )
+                if frag.strip(" \t-•")
+            ]
+            if not fragments:
+                fragments = [text_block]
+
+            rank += 1
+            role_priority = 3 if current_role == "assistant" else 4 if current_role == "user" else 5
+            for fragment_index, fragment in enumerate(fragments, start=1):
+                anchor_matches: list[dict[str, Any]] = []
+                low = fragment.lower()
+                for field_name, field_value in arguments.items():
+                    variants = _anchor_tokens(field_value)
+                    matched = [token for token in variants if token in low]
+                    if matched:
+                        anchor_matches.append({
+                            "field": str(field_name),
+                            "value": field_value,
+                            "matched_tokens": matched,
+                        })
+                blocks.append({
+                    "priority": role_priority,
+                    "recency": rank,
+                    "fragment": fragment_index,
+                    "role": current_role,
+                    "text": fragment,
+                    "anchor_matches": anchor_matches,
+                })
+
+        for raw_line in str(context or "").splitlines():
+            line = raw_line.strip()
+            if not line:
+                continue
+            low = line.lower()
+            # Priority-view section headers are metadata, not conversational text.
+            if low.startswith("priority_3_previous_assistant"):
+                flush(); current_role = "assistant"; continue
+            if low.startswith("priority_4_previous_user"):
+                flush(); current_role = "user"; continue
+            if low.startswith("priority_5_other"):
+                flush(); current_role = "other"; continue
+            payload = line.split(": ", 1)[1] if line.startswith("history:") and ": " in line else line
+            plow = payload.lower().lstrip()
+            detected = None
+            if plow.startswith(("assistant:", "agente:")):
+                detected = "assistant"
+            elif plow.startswith(("user:", "cliente:")):
+                detected = "user"
+            elif plow.startswith("system:"):
+                detected = "other"
+            if detected is not None:
+                flush()
+                current_role = detected
+                payload = payload.split(":", 1)[1].strip() if ":" in payload else payload
+            current_lines.append(payload)
+        flush()
+        return blocks
+
+    context_text = str(conversational_context or "").strip()
+    anchor_relations = _anchor_relation_candidates(context_text, known)
+    evidence_blocks = _structured_evidence_blocks(context_text, known)
+    missing_initial = [name for name in names if name not in known]
+
+    # Field-targeted views do not resolve parameters and do not add another LLM
+    # pass. They expose the SAME local evidence blocks next to the declarative
+    # semantics of each still-missing field so the single temporal reconciliation
+    # call can correlate anchors with the correct schema-defined target instead of
+    # rediscovering that mapping inside a large generic JSON blob. No field names
+    # or domain concepts are hardcoded here.
+    anchored_blocks = [block for block in evidence_blocks if block.get("anchor_matches")]
+    field_evidence_views = {
+        name: {
+            "field_spec": field_spec.get(name, {}),
+            "anchored_evidence_blocks": anchored_blocks,
+        }
+        for name in missing_initial
+    }
+
+    reconciliation_focus = {
+        "current_user_message": message,
+        "known_parameters": known,
+        "missing_parameters": missing_initial,
+        "missing_field_views": field_evidence_views,
+    }
+
     prompt = (
+        "FOCO PRINCIPAL DA RECONCILIAÇÃO (examine isto antes de qualquer contexto secundário):\n"
+        f"reconciliation_focus: {json.dumps(reconciliation_focus, ensure_ascii=False, default=str)}\n"
+        "Se um campo faltante tiver um único evidence_block ancorado semanticamente compatível com seu field_spec, resolva-o; use unresolved somente em ambiguidade real.\n\n"
         "Você é o conciliador temporal de parâmetros de uma transação ativa. "
-        "Reconstrua UM CONJUNTO COERENTE de parâmetros; não extraia cada campo de forma isolada. "
+        "Faça UMA ÚNICA VARREDURA TEMPORAL e reconstrua UM CONJUNTO COERENTE de parâmetros. "
+        "Todos os campos conhecidos e faltantes devem ser avaliados juntos; não execute uma busca isolada por campo e não faça uma segunda etapa de fallback. "
         "Não decida roteamento, confirmação nem execução.\n\n"
         "CONTRATO OBRIGATÓRIO:\n"
-        "1. O significado de cada campo vem EXCLUSIVAMENTE de parameter_schema e transaction_description, considerando principalmente a descrição semântica quando disponível. O framework não conhece conceitos de domínio por nome de campo.\n"
-        "2. A ausência de tipo ou descrição NÃO impede a extração quando o restante do contrato e o texto forem semanticamente suficientes.\n"
-        "3. A busca textual é temporal, em ordem decrescente: user_message é a fonte mais nova; depois conversational_context já vem do texto mais novo para o mais antigo.\n"
-        "3. Textos do usuário e textos explicativos do assistente podem ser usados para interpretar referências e relações entre campos. Não trate texto do contexto como uma nova afirmação do cliente; eles são contexto, não evidência autoritativa de negócio.\n"
-        "4. Para cada campo escolha: resolved = um texto determina novo valor; preserve = nenhum texto mais novo invalida o valor conhecido; clear = existe mudança textual mais nova que torna o valor conhecido incompatível/sem vínculo seguro com o novo contexto e ainda não há substituto; unresolved = não há valor conhecido nem candidato textual seguro.\n"
-        "5. Se uma fonte mais nova muda uma entidade, objeto, escopo ou outro contexto que dava sentido a campos extraídos anteriormente, REAVALIE os demais campos como conjunto. Não combine automaticamente um atributo antigo com um contexto novo só porque ambos existem.\n"
-        "6. Um valor de texto anterior pode continuar válido após uma mudança somente quando os textos, considerados em conjunto, sustentarem de forma inequívoca que ele ainda pertence ao contexto mais recente. Caso contrário use clear para o campo dependente.\n"
-        "7. Se a nova menção é inválida no mundo real, NÃO volte silenciosamente ao valor antigo. Ainda assim devolva o candidato textual mais recente como resolved; a pre-validation autoritativa é responsável por rejeitá-lo.\n"
-        "8. known_arguments é fallback de estado. Use preserve somente quando nenhum texto mais novo o contradiz ou rompe sua associação contextual.\n"
-        "9. Uma expressão só pode preencher um campo se satisfizer semanticamente type/description desse campo. Não transfira um trecho para outro campo apenas por proximidade lexical.\n"
-        "10. Se um texto recente corrige explicitamente informação anterior, a correção prevalece para os campos que o schema permite inferir; os demais devem ser reavaliados quanto à coerência com a correção.\n"
-        "11. Em ambiguidade razoável, prefira clear/unresolved a inventar uma associação. Em caso de dúvida razoável sobre a correspondência ou o valor, prefira null.\n"
-        "12. Responda SOMENTE JSON válido no formato pedido, sem markdown e sem chaves extras.\n\n"
+        "1. O significado de cada campo vem EXCLUSIVAMENTE de parameter_schema e transaction_description, principalmente a descrição semântica quando disponível. O framework não conhece conceitos de domínio por nome de campo.\n"
+        "2. A ausência de tipo ou descrição NÃO impede a extração nem a resolução quando o restante do contrato e o contexto forem semanticamente suficientes.\n"
+        "3. A resolução deve obedecer ESTA PRIORIDADE, sem inverter níveis: (1) informação explicitamente fornecida pelo usuário na mensagem atual e semanticamente compatível com o schema; (2) parâmetros já conhecidos/validados da transação; (3) respostas anteriores do assistente que apresentem relações locais entre parâmetros/atributos e que possam ter sido apoiadas por tool/evidence; (4) falas anteriores do usuário; (5) demais contexto conversacional.\n"
+        "4. Dentro de cada nível histórico, preserve a ordem temporal decrescente (mais novo -> mais antigo). Nunca escolha fonte de prioridade menor quando uma fonte de prioridade maior resolve o mesmo campo de forma coerente.\n"
+        "5. known_arguments contém o estado parcial já coletado/validado. Trate CADA parâmetro conhecido, independentemente de nome ou tipo, como possível ÂNCORA para resolver QUALQUER outro campo faltante no histórico. O significado e a compatibilidade de cada âncora vêm exclusivamente do parameter_schema. Use múltiplas âncoras simultaneamente quando disponíveis.\n"
+        "6. anchor_relation_candidates são apenas recortes do MESMO histórico que contêm representações de parâmetros conhecidos; eles servem para facilitar a correlação entre campos dentro desta única varredura. Não são uma segunda fonte, não têm prioridade própria e não autorizam inventar relações.\n"
+        "7. Quando uma âncora conhecida aparecer em um mesmo contexto local com uma ou mais informações semanticamente compatíveis com campos faltantes, use essa relação local para reconciliar TODOS os campos faltantes que puderem ser resolvidos de forma coerente na mesma resposta. Não pressuponha quais tipos de campo devem coexistir; siga apenas o schema e o contexto.\n"
+        "8. Texto anterior do assistente é CONTEXTO INTERPRETATIVO, não evidência autoritativa: pode fornecer relações locais entre quaisquer parâmetros/atributos definidos pelo schema, mas todo candidato continua sujeito à pre-validation/tool de negócio. Não descarte uma relação apenas por estar na fala do assistente. Não trate texto do contexto como uma nova afirmação do cliente.\n"
+        "9. Para cada campo escolha: resolved = texto/contexto determina novo valor; preserve = o valor conhecido continua coerente; clear = contexto mais novo rompe sua associação e não há substituto seguro; unresolved = não há candidato seguro.\n"
+        "10. Se uma fonte mais nova muda o contexto semântico que dava sentido a campos anteriores, REAVALIE os demais campos como conjunto. Não combine automaticamente informação antiga com contexto novo.\n"
+        "11. Se a nova menção é inválida no mundo real, NÃO volte silenciosamente ao valor antigo. Devolva o candidato textual mais recente como resolved e deixe a pre-validation autoritativa rejeitá-lo.\n"
+        "12. Uma expressão só pode preencher um campo se satisfizer semanticamente type/description desse campo. Não transfira um trecho para outro campo apenas por proximidade lexical.\n"
+        "13. Se o usuário corrige explicitamente informação anterior, a correção prevalece nos campos compatíveis e os demais devem ser reavaliados quanto à coerência.\n"
+        "14. unresolved é ÚLTIMO RECURSO. Antes de devolver unresolved para um campo faltante, você DEVE verificar todos os evidence_blocks na ordem de prioridade e recência e todas as anchor_relation_candidates. Se existir uma única interpretação semanticamente compatível com type/description do campo, resolva-a.\n"
+        "15. Se um parâmetro conhecido aparecer como anchor_match em um evidence_block e o MESMO bloco contiver uma única informação semanticamente compatível com um campo faltante segundo o schema, use a relação para resolved desse campo; não devolva unresolved apenas porque a informação foi apresentada pelo assistente.\n"
+        "16. Se não houver âncora útil, mas uma fonte histórica de prioridade 3 ou 4 contiver explicitamente uma informação que satisfaça semanticamente um campo faltante segundo o schema e não houver candidato concorrente de prioridade maior, resolva esse campo. Isso cobre referências posteriores em que o usuário omite um atributo porque ele já estava explícito no diálogo.\n"
+        "17. field_evidence_views reorganiza os MESMOS evidence_blocks ancorados por cada campo ainda faltante e coloca ao lado a semântica declarativa desse campo. Para cada campo faltante, examine obrigatoriamente essa visão antes de unresolved. Se um bloco ancorado contiver uma única informação compatível com field_spec e não houver concorrente de prioridade/recência maior, retorne resolved. Essa visão não é uma nova fonte nem uma segunda etapa.\n"
+        "18. Em ambiguidade REAL — dois ou mais candidatos semanticamente plausíveis sem desempate por prioridade, recência ou âncora — prefira clear/unresolved a inventar uma associação. Em caso de dúvida razoável sobre a correspondência ou o valor, prefira null/unresolved conforme o formato de saída.\n"
+        "19. Responda SOMENTE JSON válido no formato pedido, sem markdown e sem chaves extras.\n\n"
         f"transaction_tool: {tool_name}\n"
         f"transaction_description: {tool_description or ''}\n"
         f"parameter_names: {json.dumps(names, ensure_ascii=False)}\n"
+        f"known_parameters: {json.dumps(known, ensure_ascii=False, default=str)}\n"
+        f"missing_parameters: {json.dumps(missing_initial, ensure_ascii=False)}\n"
         f"pending_parameters: {json.dumps(names, ensure_ascii=False)}\n"
         f"parameter_schema: {json.dumps(field_spec, ensure_ascii=False, default=str)}\n"
-        f"known_arguments: {json.dumps(known, ensure_ascii=False, default=str)}\n"
+        f"anchor_relation_candidates: {json.dumps(anchor_relations, ensure_ascii=False, default=str)}\n"
+        f"evidence_blocks: {json.dumps(evidence_blocks, ensure_ascii=False, default=str)}\n"
+        f"field_evidence_views: {json.dumps(field_evidence_views, ensure_ascii=False, default=str)}\n"
         "conversation_sources_newest_to_oldest:\n"
+        f"priority_1_current_user_message: {message}\n"
         f"user_message: {message}\n"
-        f"conversational_context: {str(conversational_context or '').strip()}\n"
+        f"prioritized_conversational_context: {context_text}\n"
+        "RELEMBRE O FOCO PRINCIPAL: examine reconciliation_focus.missing_field_views antes de unresolved. "
+        "Um bloco ancorado único e semanticamente compatível deve produzir resolved, independentemente do papel assistant/user, respeitada a prioridade declarada.\n"
         f"Formato obrigatório: {json.dumps(output_shape, ensure_ascii=False)}"
     )
 
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diff --git a/agent_framework_oci/tests/test_contextual_reentry_transaction_parameters.py b/agent_framework_oci/tests/test_contextual_reentry_transaction_parameters.py
index 46a7b3b..af32141 100644
--- a/agent_framework_oci/tests/test_contextual_reentry_transaction_parameters.py
+++ b/agent_framework_oci/tests/test_contextual_reentry_transaction_parameters.py
@@ -42,3 +42,316 @@ async def test_contextual_reentry_separates_current_claim_from_prior_context_for
     assert "Cobrança Tamboro Mensal" in llm.prompt
     assert "user_message: é a de quatorze e noventa e nove" in llm.prompt
     assert "Não trate texto do contexto como uma nova afirmação do cliente" in llm.prompt
+
+class _TwoPassContextLLM:
+    def __init__(self):
+        self.calls = []
+
+    async def ainvoke(self, messages, **kwargs):
+        prompt = messages[-1]["content"]
+        self.calls.append(prompt)
+        # First pass: current utterance provides only the amount.
+        if "user_message: é a de vinte e cinco e cinquenta" in prompt:
+            return json.dumps({"subject": None, "valor": 25.50}, ensure_ascii=False)
+        # Second bounded pass: previous USER utterance provides the missing entity.
+        if "user_message: não reconheço esse Tamboro Mensal na minha fatura" in prompt:
+            return json.dumps({"subject": "Tamboro Mensal"}, ensure_ascii=False)
+        return "{}"
+
+
+@pytest.mark.asyncio
+async def test_contextual_reentry_second_pass_recovers_only_missing_candidate_from_prior_user_turn():
+    from agent_framework.runtime.agent_runtime import AgentRuntimeMixin
+
+    class Runtime(AgentRuntimeMixin):
+        pass
+
+    runtime = Runtime()
+    runtime.llm = _TwoPassContextLLM()
+    state = {
+        "route_decision": {
+            "metadata": {
+                "contextual_reentry": True,
+                "original_input": "é a de vinte e cinco e cinquenta",
+                "relevant_conversation_context": (
+                    "user: não reconheço esse Tamboro Mensal na minha fatura\n"
+                    "assistant: identifiquei duas cobranças de Tamboro Mensal"
+                ),
+            }
+        },
+        "sanitized_input": "é a de vinte e cinco e cinquenta",
+    }
+    out = await runtime._extract_transaction_parameters(
+        state=state,
+        tool_name="contestar_cobranca",
+        missing_parameters=["subject", "valor"],
+        known_arguments={},
+    )
+    assert float(out["valor"]) == 25.5
+    assert out["subject"] == "Tamboro Mensal"
+    assert len(runtime.llm.calls) >= 2
+
+class _CoherentTemporalLLM:
+    """Simulates the structured decisions expected from temporal reconciliation."""
+    def __init__(self):
+        self.prompts = []
+
+    async def ainvoke(self, messages, **kwargs):
+        prompt = messages[-1]["content"]
+        self.prompts.append(prompt)
+        low = prompt.lower()
+        # Product A + value X established.
+        if "user_message: na verdade é tim fashion mensal" in low:
+            return json.dumps({"fields": {
+                "subject": {"decision": "resolved", "value": "TIM Fashion Mensal", "source": "current"},
+                # Previous 14.99 was tied to the former product and must not be transplanted.
+                "valor": {"decision": "clear", "value": None, "source": "history:1"},
+            }}, ensure_ascii=False)
+        if "user_message: na verdade é produto inexistente" in low:
+            return json.dumps({"fields": {
+                # Keep the newest candidate so authoritative validation can reject it.
+                "subject": {"decision": "resolved", "value": "Produto Inexistente", "source": "current"},
+                "valor": {"decision": "clear", "value": None, "source": "history:1"},
+            }}, ensure_ascii=False)
+        if "user_message: desculpa, era tamboro mensal mesmo" in low:
+            return json.dumps({"fields": {
+                "subject": {"decision": "resolved", "value": "Tamboro Mensal", "source": "current"},
+                # Full temporal text makes the old amount coherent again with the restored product.
+                "valor": {"decision": "resolved", "value": 14.99, "source": "history:2"},
+            }}, ensure_ascii=False)
+        return json.dumps({"fields": {
+            "subject": {"decision": "preserve", "value": None, "source": "state"},
+            "valor": {"decision": "preserve", "value": None, "source": "state"},
+        }}, ensure_ascii=False)
+
+
+@pytest.mark.asyncio
+async def test_temporal_reconciliation_product_change_rechecks_old_value_as_part_of_coherent_set():
+    from agent_framework.runtime.transaction_parameters import reconcile_transaction_parameters
+
+    llm = _CoherentTemporalLLM()
+    out = await reconcile_transaction_parameters(
+        llm,
+        text="na verdade é TIM Fashion Mensal",
+        conversational_context=(
+            "history:1: user: é R$ 14,99\n"
+            "history:2: user: quero contestar Tamboro Mensal"
+        ),
+        tool_name="contestar_cobranca",
+        parameter_names=["subject", "valor"],
+        known_arguments={"subject": "Tamboro Mensal", "valor": 14.99},
+        parameter_schema={
+            "subject": {"type": "string", "description": "Nome do serviço, produto, item ou cobrança objeto da contestação."},
+            "valor": {"type": "number", "description": "Valor monetário associado ao item objeto da contestação."},
+        },
+        tool_description="Contesta uma cobrança após validação.",
+    )
+    assert out["values"] == {"subject": "TIM Fashion Mensal"}
+    assert out["clear_fields"] == ["valor"]
+    assert out["provenance"]["subject"] == "current"
+
+
+@pytest.mark.asyncio
+async def test_temporal_reconciliation_invalid_new_product_does_not_erase_history_or_fall_back_silently():
+    from agent_framework.runtime.transaction_parameters import reconcile_transaction_parameters
+
+    llm = _CoherentTemporalLLM()
+    history = (
+        "history:1: user: é R$ 14,99\n"
+        "history:2: user: quero contestar Tamboro Mensal"
+    )
+    out = await reconcile_transaction_parameters(
+        llm,
+        text="na verdade é Produto Inexistente",
+        conversational_context=history,
+        tool_name="contestar_cobranca",
+        parameter_names=["subject", "valor"],
+        known_arguments={"subject": "Tamboro Mensal", "valor": 14.99},
+        parameter_schema={
+            "subject": {"type": "string", "description": "Nome do serviço, produto, item ou cobrança objeto da contestação."},
+            "valor": {"type": "number", "description": "Valor monetário associado ao item objeto da contestação."},
+        },
+        tool_description="Contesta uma cobrança após validação.",
+    )
+    # The newest candidate stays visible for pre-validation; the old product is not silently restored.
+    assert out["values"] == {"subject": "Produto Inexistente"}
+    assert "valor" in out["clear_fields"]
+    assert "Tamboro Mensal" in llm.prompts[-1]  # history remains available to future reconciliation.
+
+
+@pytest.mark.asyncio
+async def test_temporal_reconciliation_can_restore_coherent_old_value_when_product_is_explicitly_restored():
+    from agent_framework.runtime.transaction_parameters import reconcile_transaction_parameters
+
+    llm = _CoherentTemporalLLM()
+    out = await reconcile_transaction_parameters(
+        llm,
+        text="desculpa, era Tamboro Mensal mesmo",
+        conversational_context=(
+            "history:1: user: na verdade é Produto Inexistente\n"
+            "history:2: user: é R$ 14,99\n"
+            "history:3: user: quero contestar Tamboro Mensal"
+        ),
+        tool_name="contestar_cobranca",
+        parameter_names=["subject", "valor"],
+        known_arguments={},
+        parameter_schema={
+            "subject": {"type": "string", "description": "Nome do serviço, produto, item ou cobrança objeto da contestação."},
+            "valor": {"type": "number", "description": "Valor monetário associado ao item objeto da contestação."},
+        },
+        tool_description="Contesta uma cobrança após validação.",
+    )
+    assert out["values"] == {"subject": "Tamboro Mensal", "valor": 14.99}
+    assert out["provenance"] == {"subject": "current", "valor": "history:2"}
+
+
+def test_temporal_context_priority_places_assistant_before_older_user_history():
+    from agent_framework.runtime.agent_runtime import AgentRuntimeMixin
+
+    context = (
+        "user: tem uma cobrança aqui que eu não reconheço\n"
+        "assistant: Cobrança Tamboro Mensal no valor de R$ 14,99; TIM Fashion Mensal no valor de R$ 10,00."
+    )
+    prioritized = AgentRuntimeMixin._transaction_context_priority_view(context)
+
+    assert "priority_3_previous_assistant_tool_or_evidence_context:" in prioritized
+    assert "priority_4_previous_user_utterances:" in prioritized
+    assert prioritized.index("assistant: Cobrança Tamboro Mensal") < prioritized.index("user: tem uma cobrança")
+
+
+class _AssistantRelationshipReconcilerLLM:
+    def __init__(self):
+        self.prompt = ""
+
+    async def ainvoke(self, messages, **kwargs):
+        self.prompt = messages[-1]["content"]
+        # Simula o comportamento desejado: a fala atual dá o valor, enquanto a
+        # relação item->valor está numa resposta anterior do assistant.
+        assert "user_message: é a de quatorze e noventa e nove" in self.prompt
+        assert "priority_3_previous_assistant_tool_or_evidence_context:" in self.prompt
+        assert "assistant: Cobrança Tamboro Mensal no valor de R$ 14,99" in self.prompt
+        assert "anchor_relation_candidates:" in self.prompt
+        assert "anchor[valor=14.99]" in self.prompt
+        return json.dumps({"fields": {
+            "subject": {"decision": "resolved", "value": "Tamboro Mensal", "source": "history:1"},
+            "valor": {"decision": "resolved", "value": 14.99, "source": "current"},
+        }}, ensure_ascii=False)
+
+
+@pytest.mark.asyncio
+async def test_temporal_reconciler_can_use_grounded_assistant_relationship_after_current_only_extraction_is_incomplete():
+    from agent_framework.runtime.agent_runtime import AgentRuntimeMixin
+
+    class Runtime(AgentRuntimeMixin):
+        pass
+
+    runtime = Runtime()
+    runtime.llm = _AssistantRelationshipReconcilerLLM()
+    runtime.tool_router = type("TR", (), {
+        "registry": type("REG", (), {
+            "get_tool": staticmethod(lambda name: type("CFG", (), {
+                "requires": ["subject", "valor"],
+                "args_schema": {
+                    "subject": {"type": "string", "description": "Nome do item ou cobrança a contestar."},
+                    "valor": {"type": "number", "description": "Valor monetário do item a contestar."},
+                },
+                "description": "Contesta uma cobrança após validação.",
+            })())
+        })(),
+        "resolve_execution_policy": staticmethod(lambda name, arguments=None: {
+            "operation_type": "transactional",
+            "requires": ["subject", "valor"],
+        }),
+    })()
+
+    state = {
+        "sanitized_input": "é a de quatorze e noventa e nove",
+        "user_text": "é a de quatorze e noventa e nove",
+        "route_decision": {"metadata": {
+            "contextual_reentry": True,
+            "original_input": "é a de quatorze e noventa e nove",
+            "relevant_conversation_context": (
+                "user: tem uma cobrança aqui que eu não reconheço\n"
+                "assistant: Cobrança Tamboro Mensal no valor de R$ 14,99; TIM Fashion Mensal no valor de R$ 10,00."
+            ),
+        }},
+    }
+
+    # O happy path corrente só consegue o valor; o subject fica faltando.
+    class _CurrentOnlyLLM:
+        async def ainvoke(self, messages, **kwargs):
+            return json.dumps({"valor": 14.99}, ensure_ascii=False)
+
+    original_llm = runtime.llm
+    runtime.llm = _CurrentOnlyLLM()
+    current = await runtime._extract_transaction_parameters_current_only(
+        state,
+        tool_name="contestar_cobranca",
+        missing_parameters=["subject", "valor"],
+        known_arguments={},
+    )
+    assert current == {"valor": 14.99}
+
+    runtime.llm = original_llm
+    reconciled = await runtime._reconcile_transaction_parameters(
+        state,
+        tool_name="contestar_cobranca",
+        parameter_names=["subject", "valor"],
+        known_arguments=current,
+    )
+    assert reconciled["values"]["subject"] == "Tamboro Mensal"
+    assert float(reconciled["values"]["valor"]) == 14.99
+    assert "(3) respostas anteriores do assistente" in runtime.llm.prompt
+
+class _UnifiedAnchorScanLLM:
+    def __init__(self):
+        self.calls = []
+
+    async def ainvoke(self, messages, **kwargs):
+        prompt = messages[-1]["content"]
+        self.calls.append(prompt)
+        assert "UMA ÚNICA VARREDURA TEMPORAL" in prompt
+        assert "known_parameters: {\"valor\": 14.99}" in prompt
+        assert "missing_parameters: [\"subject\", \"data\"]" in prompt
+        assert "anchor_relation_candidates:" in prompt
+        assert "anchor[valor=14.99]" in prompt
+        assert "Tamboro Mensal no valor de R$ 14,99" in prompt
+        return json.dumps({"fields": {
+            "subject": {"decision": "resolved", "value": "Tamboro Mensal", "source": "history:1"},
+            "valor": {"decision": "preserve", "value": None, "source": "state"},
+            "data": {"decision": "resolved", "value": "01/11/2025", "source": "history:1"},
+        }}, ensure_ascii=False)
+
+
+@pytest.mark.asyncio
+async def test_temporal_reconciler_single_scan_uses_all_known_fields_as_anchors_and_resolves_all_missing_fields():
+    from agent_framework.runtime.transaction_parameters import reconcile_transaction_parameters
+
+    llm = _UnifiedAnchorScanLLM()
+    result = await reconcile_transaction_parameters(
+        llm,
+        text="é a de quatorze e noventa e nove",
+        tool_name="contestar_cobranca",
+        parameter_names=["subject", "valor", "data"],
+        known_arguments={"valor": 14.99},
+        parameter_schema={
+            "subject": {"type": "string", "description": "Nome do item ou cobrança a contestar."},
+            "valor": {"type": "number", "description": "Valor monetário do item a contestar."},
+            "data": {"type": "string", "description": "Data da cobrança selecionada."},
+        },
+        tool_description="Contesta uma cobrança após validação.",
+        conversational_context=(
+            "priority_3_previous_assistant_tool_or_evidence_context:\n"
+            "history:1: assistant: Cobrança Tamboro Mensal no valor de R$ 14,99 no dia 01/11/2025 * "
+            "TIM Fashion Mensal no valor de R$ 10,00 no dia 01/11/2025.\n"
+            "priority_4_previous_user_utterances:\n"
+            "history:2: user: tem uma cobrança aqui que eu não reconheço"
+        ),
+    )
+
+    assert len(llm.calls) == 1
+    assert result["values"]["subject"] == "Tamboro Mensal"
+    assert float(result["values"]["valor"]) == 14.99
+    assert result["values"]["data"] == "01/11/2025"
+    assert result["provenance"]["subject"] == "history:1"
+
diff --git a/agent_framework_oci/tests/test_transaction_parameter_llm_precedence.py b/agent_framework_oci/tests/test_transaction_parameter_llm_precedence.py
index fe2ed05..c15adcb 100644
--- a/agent_framework_oci/tests/test_transaction_parameter_llm_precedence.py
+++ b/agent_framework_oci/tests/test_transaction_parameter_llm_precedence.py
@@ -643,3 +643,98 @@ intents: []
     decision = await router.route(state)
     assert decision.metadata["transaction_confirmation_decision"] == "confirm"
     assert decision.metadata["transaction_confirmation_source"] == "deterministic"
+
+@pytest.mark.asyncio
+async def test_collecting_preserves_resolved_required_fields_and_only_extracts_currently_missing():
+    class Runtime(_Runtime):
+        def __init__(self):
+            super().__init__()
+            self.pending_seen = None
+
+        async def _extract_transaction_parameters(
+            self, state, *, tool_name, missing_parameters, known_arguments=None
+        ):
+            self.pending_seen = list(missing_parameters)
+            # Simulate the value extracted for the only missing field. A resolved
+            # required field must not be offered back to the semantic extractor.
+            return {"reason": "desisti da compra"}
+
+    runtime = Runtime()
+    state = {
+        "user_text": "desisti da compra",
+        "sanitized_input": "desisti da compra",
+        "transaction_status": "COLLECTING_PARAMETERS",
+        "missing_parameters": ["reason"],
+        "mcp_tools": ["solicitar_devolucao"],
+        "active_transaction": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {"order_id": "PED-1001"},
+            "status": "COLLECTING_PARAMETERS",
+            "parameter_schema": {"order_id": "string", "reason": "string"},
+            "tool_description": "Abre uma solicitação de devolução de pedido.",
+        },
+        "selected_tool_call": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {"order_id": "PED-1001"},
+        },
+        "route_decision": {"metadata": {}},
+        "route": "support_agent",
+        "intent": "state:COLLECTING_SUPPORT_PARAMETERS",
+    }
+
+    result = await runtime.execute_tools_for_intent(state)
+    assert runtime.pending_seen == ["reason"]
+    assert state["pending_tool_call"]["arguments"]["order_id"] == "PED-1001"
+    assert state["pending_tool_call"]["arguments"]["reason"] == "desisti da compra"
+    assert result[-1]["awaiting_confirmation"] is True
+
+@pytest.mark.asyncio
+async def test_correction_of_missing_numeric_value_does_not_reopen_resolved_text_entity():
+    class Runtime(_Runtime):
+        def __init__(self):
+            super().__init__()
+            self.pending_seen = None
+
+        async def _extract_transaction_parameters(
+            self, state, *, tool_name, missing_parameters, known_arguments=None
+        ):
+            self.pending_seen = list(missing_parameters)
+            # If subject were incorrectly offered again, a semantic extractor
+            # could reinterpret the monetary phrase as an entity. The runtime
+            # contract must expose only the missing numeric field here.
+            out = {"valor": 19.99}
+            if "subject" in missing_parameters:
+                out["subject"] = "cobrança de R$ 19,99"
+            return out
+
+    runtime = Runtime()
+    state = {
+        "user_text": "desculpa é a de dezenove e noventa e nove",
+        "sanitized_input": "desculpa é a de dezenove e noventa e nove",
+        "transaction_status": "COLLECTING_PARAMETERS",
+        "missing_parameters": ["valor"],
+        "mcp_tools": ["solicitar_devolucao"],
+        "active_transaction": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {"order_id": "PED-1001"},
+            "status": "COLLECTING_PARAMETERS",
+            "parameter_schema": {"order_id": "string", "reason": "string", "valor": "number"},
+        },
+        "selected_tool_call": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {"order_id": "PED-1001"},
+        },
+        "route_decision": {"metadata": {}},
+        "route": "support_agent",
+        "intent": "state:COLLECTING_SUPPORT_PARAMETERS",
+    }
+    # This synthetic tool doesn't require valor, so exercise the extraction
+    # contract directly with the same resolved-text/missing-number shape.
+    out = await runtime._extract_transaction_parameters(
+        state,
+        tool_name="solicitar_devolucao",
+        missing_parameters=["valor"],
+        known_arguments={"subject": "Tamboro Mensal"},
+    )
+    assert runtime.pending_seen == ["valor"]
+    assert out == {"valor": 19.99}
diff --git a/agent_framework_oci/tests/test_transactional_tool_flow.py b/agent_framework_oci/tests/test_transactional_tool_flow.py
index 48f6b0f..71c03b0 100644
--- a/agent_framework_oci/tests/test_transactional_tool_flow.py
+++ b/agent_framework_oci/tests/test_transactional_tool_flow.py
@@ -1283,3 +1283,94 @@ async def test_prevalidation_parameter_message_is_used_once_without_changing_tra
     # One-shot: subsequent clarification falls back to the normal prompt.
     assert runtime.transaction_clarification_message(state) != expected
     assert "transaction_parameter_message_override" not in state
+
+class _TemporalFallbackRuntime(AgentRuntimeMixin):
+    def __init__(self):
+        from types import SimpleNamespace
+        self.calls = []
+        self.llm = None
+        self.tool_router = SimpleNamespace(
+            registry=SimpleNamespace(
+                get_tool=lambda name: SimpleNamespace(
+                    requires=["subject"],
+                    args_schema={"subject": {"type": "string", "description": "Nome do serviço ou VAS alvo do cancelamento."}},
+                    description="Cancela o serviço VAS selecionado pelo cliente.",
+                    confirmation_required=True,
+                    tool_type="transactional",
+                )
+            ),
+            resolve_execution_policy=lambda name, arguments=None: {
+                "operation_type": "transactional",
+                "require_confirmation": True,
+                "requires": ["subject"],
+                "pre_validation": {"enabled": True, "tool": "validar_vas_subject", "fail_open": False},
+            },
+        )
+
+    async def _extract_transaction_parameters_current_only(self, state, *, tool_name, missing_parameters, known_arguments=None):
+        # Simula o collector tradicional interpretando literalmente a fala atual.
+        return {"subject": "dezenove e noventa e nove"}
+
+    async def _reconcile_transaction_parameters(self, state, *, tool_name, parameter_names, known_arguments=None):
+        # Simula o reconciliador temporal usando tools.yaml + contexto newest->oldest.
+        return {
+            "values": {"subject": "Tamboro Mensal"},
+            "decisions": {"subject": "resolved"},
+            "provenance": {"subject": "history:2"},
+            "clear_fields": [],
+        }
+
+    async def _call_mcp_tool(self, tool_name, arguments, state):
+        self.calls.append((tool_name, dict(arguments)))
+        if tool_name == "validar_vas_subject":
+            subject = arguments.get("subject")
+            if subject == "Tamboro Mensal":
+                return {"ok": True, "tool_name": tool_name, "result": {"eligible": True, "status": "ELIGIBLE"}}
+            return {"ok": True, "tool_name": tool_name, "result": {
+                "eligible": False,
+                "status": "NEEDS_PARAMETER",
+                "parameter": "subject",
+                "reason": "subject_not_resolved",
+            }}
+        return {"ok": True, "tool_name": tool_name, "result": {"status": "OK"}}
+
+
+@pytest.mark.asyncio
+async def test_temporal_reconciler_is_fallback_after_traditional_candidate_fails_prevalidation():
+    runtime = _TemporalFallbackRuntime()
+    state = {
+        "user_text": "é a de dezenove e noventa e nove",
+        "sanitized_input": "é a de dezenove e noventa e nove",
+        "route": "contestacao_agent",
+        "intent": "state:COLLECTING_CONTESTACAO_PARAMETERS",
+        "transaction_status": "COLLECTING_PARAMETERS",
+        "selected_tool_call": {"tool_name": "cancelar_vas_avulso", "arguments": {}},
+        "active_transaction": {
+            "transaction_id": "tx-1",
+            "tool_name": "cancelar_vas_avulso",
+            "arguments": {},
+            "status": "COLLECTING_PARAMETERS",
+            "started_from_intent": "contas_vas_cancel",
+            "requires": ["subject"],
+            "parameter_schema": {"subject": {"type": "string", "description": "Nome do serviço ou VAS alvo do cancelamento."}},
+            "tool_description": "Cancela o serviço VAS selecionado pelo cliente.",
+            "parameter_conversational_context": (
+                "user: não reconheço esse Tamboro Mensal na minha fatura\n"
+                "assistant: identifiquei Tamboro Mensal por R$ 14,99 e R$ 19,99"
+            ),
+        },
+        "context": {},
+    }
+
+    result = await runtime.execute_tools_for_intent(state, tools=[])
+
+    validations = [(name, args.get("subject")) for name, args in runtime.calls if name == "validar_vas_subject"]
+    assert validations == [
+        ("validar_vas_subject", "dezenove e noventa e nove"),
+        ("validar_vas_subject", "Tamboro Mensal"),
+    ]
+    assert state["transaction_parameter_collection"]["mode"] == "current_turn"
+    assert state["transaction_parameter_reconciliation"]["trigger"] == "prevalidation_needs_parameter"
+    assert state["pending_tool_call"]["arguments"]["subject"] == "Tamboro Mensal"
+    assert state["transaction_status"] == "AWAITING_CONFIRMATION"
+    assert result[-1]["awaiting_confirmation"] is True
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diff --git a/contas_mcp/servers/contas_mcp_server/__pycache__/main.cpython-313.pyc b/contas_mcp/servers/contas_mcp_server/__pycache__/main.cpython-313.pyc
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diff --git a/contas_mcp/servers/contas_mcp_server/main.py b/contas_mcp/servers/contas_mcp_server/main.py
index 212d473..7ef59f5 100644
--- a/contas_mcp/servers/contas_mcp_server/main.py
+++ b/contas_mcp/servers/contas_mcp_server/main.py
@@ -151,9 +151,26 @@ def _invoice_subject_catalog(args: dict[str, Any]) -> list[dict[str, Any]]:
         key = _norm_invoice_name(canonical)
         if not key:
             return
-        item = found.setdefault(key, {"name": canonical, "value": value, "category": str(category or "").strip(), "contestable": contestable})
-        if item.get("value") in (None, "") and value not in (None, ""):
-            item["value"] = value
+        item = found.setdefault(key, {
+            "name": canonical,
+            "value": None,
+            "values": [],
+            "category": str(category or "").strip(),
+            "contestable": contestable,
+        })
+        if value not in (None, ""):
+            # Preserve every distinct billed value for the canonical subject.
+            # A subject may occur more than once on the same invoice; in that case
+            # no single value is authoritative until the user-selected amount is
+            # validated against this set.
+            raw = str(value).strip().replace(",", ".")
+            try:
+                normalized_value: Any = float(raw)
+            except (TypeError, ValueError):
+                normalized_value = str(value).strip()
+            if normalized_value not in item["values"]:
+                item["values"].append(normalized_value)
+            item["value"] = item["values"][0] if len(item["values"]) == 1 else None
         if not item.get("category") and category:
             item["category"] = str(category).strip()
         if item.get("contestable") is None and contestable is not None:
@@ -283,6 +300,13 @@ def _preflight_subject(name: str, args: dict[str, Any]) -> dict[str, Any] | None
             subject = canonical
             if explicit.get("value") not in (None, ""):
                 args["resolved_value"] = str(explicit.get("value"))
+                args["resolved_value_source"] = "invoice_unique_subject_value"
+            else:
+                # Multiple billed occurrences for the same subject (or no billed
+                # value) mean the subject alone cannot resolve an amount. Never
+                # preserve a stale/user-claimed value as resolved_value.
+                args.pop("resolved_value", None)
+                args.pop("resolved_value_source", None)
             category = str(explicit.get("category") or "").strip()
             if category:
                 args["resolved_category"] = category
@@ -334,8 +358,21 @@ def _preflight_subject(name: str, args: dict[str, Any]) -> dict[str, Any] | None
             args.setdefault("item_msisdn", resolved.msisdn)
         if resolved.charge_date:
             args.setdefault("charge_date", resolved.charge_date)
-        if getattr(resolved, "value", None) is not None:
-            args.setdefault("resolved_value", str(resolved.value))
+        subject_key = _norm_invoice_name(resolved.canonical_name)
+        subject_record = next((
+            item for item in _invoice_subject_catalog(args)
+            if _norm_invoice_name(item.get("name")) == subject_key
+        ), None)
+        unique_subject_value = subject_record.get("value") if isinstance(subject_record, dict) else None
+        if unique_subject_value not in (None, ""):
+            args["resolved_value"] = str(unique_subject_value)
+            args["resolved_value_source"] = "invoice_unique_subject_value"
+        else:
+            # Do not select one arbitrary occurrence when the same subject has
+            # multiple billed values. The user-selected value must be checked by
+            # CVAL against the subject before it can become resolved_value.
+            args.pop("resolved_value", None)
+            args.pop("resolved_value_source", None)
         # Paridade do backend original: se o cliente pediu cancelamento avulso,
         # mas a própria fatura classifica o item como estratégico/bundle, não
         # executamos a operação errada. A resolução determinística do domínio
@@ -1040,7 +1077,14 @@ async def _validate_contestation(args: dict[str, Any]) -> dict[str, Any]:
                 "parameter": "subject",
                 "reason": "subject_not_resolved",
                 "subject": args.get("resolved_subject") or args.get("subject"),
-                "resolved_value": requested_value,
+                # requested_value is only a candidate while the subject itself is
+                # unresolved. It must never be promoted to resolved_value.
+                "candidate_value": requested_value,
+                "resolved_value": None,
+                "clear_fields": [
+                    "resolved_subject", "resolved_value", "resolved_category",
+                    "item_msisdn", "charge_date",
+                ],
                 "validation_log": validation_log,
                 "items": validated,
                 "metadata": {
@@ -1082,7 +1126,14 @@ async def _validate_contestation(args: dict[str, Any]) -> dict[str, Any]:
                 "reason": "CVAL",
                 "recoverable_reason": "amount_not_supported_by_invoice",
                 "subject": canonical_subject,
-                "resolved_value": billed,
+                # The claimed value was rejected. Keep it only as diagnostic
+                # candidate data. The billed value may be shown to the user but
+                # is not persisted as the selected resolved_value until the next
+                # candidate is validated relationally against this subject.
+                "candidate_value": requested_value,
+                "billed_value": billed,
+                "resolved_value": None,
+                "clear_fields": ["resolved_value"],
                 "parameter_message": message,
                 "validation_log": validation_log,
                 "items": validated,
@@ -1105,14 +1156,25 @@ async def _validate_contestation(args: dict[str, Any]) -> dict[str, Any]:
             "items": validated,
             "metadata": {"side_effect_free": True, "target_tool": args.get("target_tool") or "contestar_cobranca", "guardrail_code": "CVAL"},
         }
+    canonical_subject = str(args.get("resolved_subject") or args.get("subject") or "").strip()
     return {
         "eligible": True,
         "status": "ELIGIBLE",
-        "subject": args.get("resolved_subject") or args.get("subject"),
+        "subject": canonical_subject,
+        # Only the successful subject+amount CVAL relationship promotes the
+        # candidate into resolved_value.
         "resolved_value": requested_value,
         "category": args.get("resolved_category"),
         "validation_log": validation_log,
         "items": validated,
+        "transaction_decision": {
+            "resolved_arguments": {
+                "subject": canonical_subject,
+                "resolved_subject": canonical_subject,
+                "resolved_value": requested_value,
+                "resolved_value_source": "contestation_cval_subject_amount",
+            }
+        },
         "metadata": {"side_effect_free": True, "target_tool": args.get("target_tool") or "contestar_cobranca", "guardrail_code": "CVAL"},
     }
 
diff --git a/docs/FIX_CONTESTATION_RELATIONAL_RESOLUTION_20260907.md b/docs/FIX_CONTESTATION_RELATIONAL_RESOLUTION_20260907.md
new file mode 100644
index 0000000..6410712
--- /dev/null
+++ b/docs/FIX_CONTESTATION_RELATIONAL_RESOLUTION_20260907.md
@@ -0,0 +1,15 @@
+# Correção — resolução relacional de contestação
+
+## Regra
+
+`resolved_value` representa um valor efetivamente resolvido/validado para o `subject` da transação.
+Um valor apenas informado pelo usuário é `candidate_value` até a pré-validação autoritativa confirmar a relação `subject + valor` contra a evidência da fatura.
+
+## Invariantes
+
+1. Um valor divergente não é promovido a `resolved_value`.
+2. Se o mesmo subject aparece com vários valores na fatura, o subject sozinho não escolhe um valor arbitrário.
+3. Se dois produtos diferentes têm o mesmo valor, o valor não substitui um subject já identificado por evidência mais forte do usuário.
+4. Quando a pré-validação rejeita um parâmetro, ela pode declarar `clear_fields` para invalidar derivados dependentes; o framework aplica essa lista sem conhecer semântica de domínio.
+5. A extração do turno atual ocorre antes da reconciliação. A reconciliação pode canonicalizar o candidato, mas não apagá-lo antes da pré-validação.
+6. Somente uma validação relacional bem-sucedida promove o candidato a `resolved_value`.
diff --git a/docs/FIX_RECONCILIACAO_REWORK_MINIMO_20260907.md b/docs/FIX_RECONCILIACAO_REWORK_MINIMO_20260907.md
new file mode 100644
index 0000000..dd481db
--- /dev/null
+++ b/docs/FIX_RECONCILIACAO_REWORK_MINIMO_20260907.md
@@ -0,0 +1,19 @@
+# Rework mínimo da reconciliação temporal — 2026-09-07
+
+## Princípios
+
+1. Extração do turno atual é uma etapa curta, sem histórico.
+2. Reconciliação temporal só roda se required fields continuarem faltando.
+3. Candidate estrutural só existe quando há um único evidence block ancorado por parâmetro conhecido.
+4. Candidate estrutural nunca é resolved; exige pre-validation configurada.
+5. Não existe fallback baseado apenas em uma fala histórica única.
+6. A pre-validation/CVAL é a autoridade para canonicalização e relação subject+valor.
+7. Intent shift genérico não encerra transação ativa; abandono explícito pode encerrar e rerotear.
+
+## Cenário 08
+
+Mensagem atual -> valor 14.99 (current-only extraction) -> histórico ancorado -> candidate subject -> CVAL -> subject canônico -> confirmação.
+
+## Cenário 16
+
+Subject preservado -> valor 25.50 candidato -> CVAL rejeita relação -> valor continua pendente -> valor 19.99 -> CVAL valida relação -> confirmação. Uma fala como "isso mesmo, pode cancelar" permanece na transação; abandono explícito como "esquece isso, quero ver minha fatura" pode rerotear.
diff --git a/tests/migration/test_contestation_resolved_value_relational.py b/tests/migration/test_contestation_resolved_value_relational.py
new file mode 100644
index 0000000..22f9e44
--- /dev/null
+++ b/tests/migration/test_contestation_resolved_value_relational.py
@@ -0,0 +1,90 @@
+from __future__ import annotations
+
+import asyncio
+
+from contas_mcp.servers.contas_mcp_server import main
+
+
+def _analysis():
+    return {
+        "currentInvoice": [
+            {
+                "type": "servicos_contratados_de_parceiros",
+                "items": [
+                    {"desc": "Tamboro Mensal", "value": "14.99", "contestable": True, "classe": "avulso"},
+                    {"desc": "Tamboro Mensal", "value": "19.99", "contestable": True, "classe": "avulso"},
+                    {"desc": "Outro Produto", "value": "19.99", "contestable": True, "classe": "avulso"},
+                ],
+            }
+        ]
+    }
+
+
+def test_subject_catalog_does_not_choose_arbitrary_value_for_repeated_subject():
+    catalog = main._invoice_subject_catalog({"billing_analysis": _analysis()})
+    tamboro = next(x for x in catalog if x["name"] == "Tamboro Mensal")
+    assert sorted(tamboro["values"]) == [14.99, 19.99]
+    assert tamboro["value"] is None
+
+
+def test_preflight_does_not_resolve_value_from_subject_when_subject_has_multiple_values(monkeypatch):
+    class DummyClient:
+        def billing_analysis(self, _msisdn):
+            return _analysis()
+
+    class DummyService:
+        client = DummyClient()
+
+    monkeypatch.setattr(main, "service", DummyService())
+    args = {
+        "msisdn": "11999999999",
+        "subject": "Tamboro Mensal",
+        "query": "não reconheço esse Tamboro Mensal",
+        "billing_analysis": _analysis(),
+        "resolved_value": "25.5",
+    }
+    # The resolver may continue to normal validation, but it must not retain an
+    # arbitrary/stale resolved_value just because the subject matched.
+    main._preflight_subject("contestar_cobranca", args)
+    assert args["subject"] == "Tamboro Mensal"
+    assert args.get("resolved_value") is None
+
+
+def test_invalid_amount_is_candidate_not_resolved(monkeypatch):
+    async def no_enrich(_name, _args):
+        return None
+    monkeypatch.setattr(main, "_enrich_invoice_context", no_enrich)
+    monkeypatch.setattr(main, "_preflight_subject", lambda *_a, **_k: None)
+    args = {
+        "msisdn": "11999999999",
+        "subject": "Tamboro Mensal",
+        "valor": 25.5,
+        "billing_analysis": _analysis(),
+        "target_tool": "contestar_cobranca",
+    }
+    result = asyncio.run(main._validate_contestation(args))
+    assert result["eligible"] is False
+    assert result["status"] == "NEEDS_PARAMETER"
+    assert result["parameter"] == "valor"
+    assert result["candidate_value"] == 25.5
+    assert result["resolved_value"] is None
+
+
+def test_valid_amount_is_resolved_only_after_subject_amount_validation(monkeypatch):
+    async def no_enrich(_name, _args):
+        return None
+    monkeypatch.setattr(main, "_enrich_invoice_context", no_enrich)
+    monkeypatch.setattr(main, "_preflight_subject", lambda *_a, **_k: None)
+    args = {
+        "msisdn": "11999999999",
+        "subject": "Tamboro Mensal",
+        "valor": 19.99,
+        "billing_analysis": _analysis(),
+        "target_tool": "contestar_cobranca",
+    }
+    result = asyncio.run(main._validate_contestation(args))
+    assert result["eligible"] is True
+    assert result["resolved_value"] == 19.99
+    resolved = result["transaction_decision"]["resolved_arguments"]
+    assert resolved["subject"] == "Tamboro Mensal"
+    assert resolved["resolved_value"] == 19.99
diff --git a/tests/migration/test_contestation_subject_entity_resolution.py b/tests/migration/test_contestation_subject_entity_resolution.py
index f43481f..de6187e 100644
--- a/tests/migration/test_contestation_subject_entity_resolution.py
+++ b/tests/migration/test_contestation_subject_entity_resolution.py
@@ -50,6 +50,8 @@ def test_validator_turns_unresolved_subject_into_recoverable_parameter_request(m
     assert result["status"] == "NEEDS_PARAMETER"
     assert result["parameter"] == "subject"
     assert result["reason"] == "subject_not_resolved"
-    assert result["resolved_value"] == 10.0
+    assert result["candidate_value"] == 10.0
+    assert result["resolved_value"] is None
+    assert "resolved_value" in result["clear_fields"]
     assert result["metadata"]["entity_resolution"] == "invoice_evidence"
     assert "error" not in result
diff --git a/tests/migration/test_requested_tools_parity_pente_fino.py b/tests/migration/test_requested_tools_parity_pente_fino.py
index da631a7..ffc05b8 100644
--- a/tests/migration/test_requested_tools_parity_pente_fino.py
+++ b/tests/migration/test_requested_tools_parity_pente_fino.py
@@ -113,7 +113,7 @@ async def test_validar_contestacao_usa_mesma_cval_e_rejeita_valor_acima_da_fatur
 
 
 @pytest.mark.asyncio
-async def test_validar_contestacao_aprova_quando_item_e_valor_sao_comprovados(monkeypatch):
+async def test_validar_contestacao_rejeita_valor_que_nao_pertence_ao_item(monkeypatch):
     billing = json.loads((ROOT / "app/domain/contas/fixtures/divergencia.json").read_text(encoding="utf-8"))
 
     async def no_enrich(name, args):
@@ -127,8 +127,12 @@ async def test_validar_contestacao_aprova_quando_item_e_valor_sao_comprovados(mo
         "motivo": "quero contestar TIM Fashion Mensal",
         "billing_analysis": billing,
     })
-    assert out["eligible"] is True
-    assert out["status"] == "ELIGIBLE"
+    assert out["eligible"] is False
+    assert out["status"] == "NEEDS_PARAMETER"
+    assert out["parameter"] == "valor"
+    assert out["candidate_value"] == 50
+    assert out["billed_value"] == "10"
+    assert out["resolved_value"] is None
 
 
 def test_termino_desconto_e_valor_divergente_preservam_semantica_do_original():
diff --git a/tests/migration/test_subject_entity_resolution_all_domains.py b/tests/migration/test_subject_entity_resolution_all_domains.py
index 4711601..d23741a 100644
--- a/tests/migration/test_subject_entity_resolution_all_domains.py
+++ b/tests/migration/test_subject_entity_resolution_all_domains.py
@@ -274,6 +274,9 @@ async def test_contestation_wrong_amount_is_recoverable_with_invoice_amount(monk
     assert result['eligible'] is False
     assert result['status'] == 'NEEDS_PARAMETER'
     assert result['parameter'] == 'valor'
-    assert result['resolved_value'] == '14.99'
+    assert result['candidate_value'] == '29.98'
+    assert result['billed_value'] == '14.99'
+    assert result['resolved_value'] is None
+    assert 'resolved_value' in result['clear_fields']
     assert 'R$ 14,99' in result['parameter_message']
     assert 'R$ 29,98' in result['parameter_message']