feat(engine): 添加运行时上下文支持并重构工具迭代限制

添加 RuntimeContext 类用于捕获模型运行时的日期时间信息，
包括UTC时间、本地时间和时区信息，并在系统提示中显示这些信息。

同时增加最大上下文消息数和工具迭代次数的配置选项，
将验证服务从引擎加载器中移除，并更新相关的数据结构和接口。

BREAKING CHANGE: 移除了验证服务，相关字段被替换为证据状态和接受状态。

- 添加 RuntimeContext 类和相关渲染方法
- 增加 max_context_messages 和 max_tool_iterations 配置
- 移除 ValidationService 相关代码
- 更新消息记录中的验证状态字段
- 添加原始工具调用检测和回退处理

app-instance/backend/beaver/engine/context/__init__.py

@@ -4,6 +4,7 @@ from .builder import (
     ContextBuildInput,
     ContextBuildResult,
     ContextBuilder,
+    RuntimeContext,
     SessionContext,
     SkillContext,
 )
@@ -12,6 +13,7 @@ __all__ = [
     "ContextBuildInput",
     "ContextBuildResult",
     "ContextBuilder",
+    "RuntimeContext",
     "SessionContext",
     "SkillContext",
 ]

app-instance/backend/beaver/engine/context/builder.py

@@ -80,6 +80,16 @@ class SessionContext:
     parent_session_id: str | None = None
 
 
+@dataclass(slots=True)
+class RuntimeContext:
+    """Per-run runtime facts that should be visible to the model."""
+
+    utc_datetime: str
+    local_datetime: str
+    timezone: str | None = None
+    utc_offset: str | None = None
+
+
 @dataclass(slots=True)
 class ContextBuildInput:
     """一次上下文构建所需的全部输入。
@@ -103,6 +113,7 @@ class ContextBuildInput:
     memory_snapshot: MemorySnapshot | None = None
     activated_skills: list[SkillContext] = field(default_factory=list)
     session_context: SessionContext | None = None
+    runtime_context: RuntimeContext | None = None
     execution_context: str | None = None
     extra_sections: list[str] = field(default_factory=list)
 
@@ -143,9 +154,10 @@ class ContextBuilder:
         1. Beaver user-facing assistant identity
         2. base system prompt
         3. session metadata
-        4. execution context
-        5. frozen memory snapshot
-        6. extra sections
+        4. runtime date/time
+        5. execution context
+        6. frozen memory snapshot
+        7. extra sections
 
         这样设计的原因：
         - 身份与总规则要最靠前
@@ -164,6 +176,10 @@ class ContextBuilder:
         if session_section:
             sections.append(session_section)
 
+        runtime_section = self._render_runtime_section(build_input.runtime_context)
+        if runtime_section:
+            sections.append(runtime_section)
+
         execution_context = (build_input.execution_context or "").strip()
         if execution_context:
             sections.append(f"# Execution Context\n\n{execution_context}")
@@ -347,6 +363,31 @@ class ContextBuilder:
             return None
         return "# Current Session\n\n" + "\n".join(rows)
 
+    def _render_runtime_section(self, runtime_context: RuntimeContext | None) -> str | None:
+        """Render date/time facts captured for the current model run."""
+
+        if runtime_context is None:
+            return None
+
+        rows: list[str] = []
+        if runtime_context.utc_datetime:
+            rows.append(f"Current UTC time: {runtime_context.utc_datetime}")
+        if runtime_context.local_datetime:
+            rows.append(f"Current local time: {runtime_context.local_datetime}")
+        if runtime_context.timezone:
+            rows.append(f"Local timezone: {runtime_context.timezone}")
+        if runtime_context.utc_offset:
+            rows.append(f"Local UTC offset: {runtime_context.utc_offset}")
+
+        if not rows:
+            return None
+        return (
+            "# Current Date and Time\n\n"
+            + "\n".join(rows)
+            + "\n\nUse this section as authoritative for relative date/time references such as "
+            '"today", "tomorrow", "now", "this week", and "next month".'
+        )
+
     def build_skill_activation_messages(self, activated_skills: list[SkillContext]) -> list[dict[str, str]]:
         """把已激活 skill 转成显式消息。
 

app-instance/backend/beaver/engine/loader.py

@@ -24,7 +24,7 @@ from beaver.skills.learning.eval import SkillDraftEvaluator
 from beaver.skills.publisher import SkillPublisher
 from beaver.skills.reviews import ReviewService
 from beaver.skills.specs import SkillSpecStore
-from beaver.tasks import TaskExecutionPlanner, TaskService, ValidationService
+from beaver.tasks import TaskExecutionPlanner, TaskService
 from beaver.tasks.skill_resolver import TaskSkillResolver
 from beaver.skills import SkillAssembler, SkillsLoader
 from beaver.tools import ObjectBackedTool, ToolAssembler, ToolExecutor, ToolRegistry
@@ -91,7 +91,6 @@ class EngineLoadResult:
     task_skill_resolver: TaskSkillResolver | None = None
     task_service: TaskService | None = None
     task_execution_planner: TaskExecutionPlanner | None = None
-    validation_service: ValidationService | None = None
     mcp_manager: MCPConnectionManager | None = None
     mcp_report: dict[str, dict] = field(default_factory=dict)
     closeables: list[tuple[str, Callable[[], None]]] = field(default_factory=list, repr=False)
@@ -166,7 +165,6 @@ class EngineLoader:
         task_skill_resolver: TaskSkillResolver | None = None,
         task_service: TaskService | None = None,
         task_execution_planner: TaskExecutionPlanner | None = None,
-        validation_service: ValidationService | None = None,
     ) -> None:
         self.config = config or load_config(workspace=workspace, config_path=config_path)
         configured_workspace = self.config.agents_defaults.workspace
@@ -192,7 +190,6 @@ class EngineLoader:
         self._task_skill_resolver = task_skill_resolver
         self._task_service = task_service
         self._task_execution_planner = task_execution_planner
-        self._validation_service = validation_service
 
     def load(self) -> EngineLoadResult:
         """装配当前主链需要的最小 runtime 对象。"""
@@ -276,7 +273,6 @@ class EngineLoader:
         )
         task_service = self._task_service or TaskService(workspace / "tasks")
         task_execution_planner = self._task_execution_planner or TaskExecutionPlanner(task_skill_resolver=task_skill_resolver)
-        validation_service = self._validation_service or ValidationService()
         mcp_manager = MCPConnectionManager(
             self.config.tools.mcp_servers,
             authz_config=self.config.authz,
@@ -311,7 +307,6 @@ class EngineLoader:
             task_skill_resolver=task_skill_resolver,
             task_service=task_service,
             task_execution_planner=task_execution_planner,
-            validation_service=validation_service,
             mcp_manager=mcp_manager,
         )
         if self._session_manager is None:

app-instance/backend/beaver/engine/loop.py

@@ -4,12 +4,15 @@ from __future__ import annotations
 
 import asyncio
 import json
+import os
+import re
 from dataclasses import dataclass, field
 from datetime import datetime, timezone
 from typing import Any
 from uuid import uuid4
+from zoneinfo import ZoneInfo, ZoneInfoNotFoundError
 
-from beaver.engine.context import ContextBuildInput, SessionContext, SkillContext
+from beaver.engine.context import ContextBuildInput, RuntimeContext, SessionContext, SkillContext
 from beaver.memory.runs import RunRecord, SkillEffectRecord
 from beaver.skills.learning import RunReceiptContext
 from beaver.skills.catalog.utils import strip_frontmatter
@@ -26,6 +29,17 @@ TOOL_FAILURE_GUIDANCE_PROMPT = (
     "Use available materials, state uncertainty clearly, and provide partial confirmed results."
 )
 
+RAW_TOOL_CALL_FALLBACK = (
+    "The run reached the configured tool-call limit before producing a reliable final answer. "
+    "The model attempted another tool call instead of answering, so the raw tool call was suppressed. "
+    "Please request a revision to continue the task."
+)
+
+_RAW_TOOL_CALL_RE = re.compile(
+    r"^\s*<tool_call\b[\s\S]*?</tool_call>\s*$|^\s*<function=[^>]+>[\s\S]*?</function>\s*$",
+    re.IGNORECASE,
+)
+
 
 @dataclass(slots=True)
 class AgentProfile:
@@ -35,8 +49,9 @@ class AgentProfile:
     system_prompt: str = ""
     default_model: str = "gpt-4.1-mini"
     max_tokens: int = 4096
+    max_context_messages: int = 1000
     temperature: float = 0.2
-    max_tool_iterations: int = 8
+    max_tool_iterations: int = 30
 
 
 @dataclass(slots=True)
@@ -446,7 +461,7 @@ class AgentLoop:
                 *(pinned_skill_contexts or []),
                 *self._load_pinned_skill_contexts(skills_loader, pinned_skill_names or []),
             ]
-            if not include_skill_assembly or thinking_enabled is False:
+            if not include_skill_assembly:
                 activated_skills = self._merge_skill_contexts(pinned_skills, [])
             else:
                 skill_query = skill_selection_context or task
@@ -512,8 +527,6 @@ class AgentLoop:
 
             if not include_tools:
                 selected_tool_specs = []
-            elif thinking_enabled is False:
-                selected_tool_specs = tool_registry.list_specs()
             else:
                 selected_tool_specs = await tool_assembler.assemble(
                     task_description=task,
@@ -543,7 +556,10 @@ class AgentLoop:
 
             build_input = ContextBuildInput(
                 base_system_prompt=self.profile.system_prompt,
-                history=session_manager.get_history(resolved_session_id),
+                history=session_manager.get_history(
+                    resolved_session_id,
+                    max_messages=max(1, self.profile.max_context_messages),
+                ),
                 current_user_input=task,
                 memory_snapshot=memory_snapshot,
                 activated_skills=activated_skills,
@@ -554,6 +570,7 @@ class AgentLoop:
                     user_id=user_id,
                     parent_session_id=parent_session_id,
                 ),
+                runtime_context=self._current_runtime_context(),
                 execution_context=execution_context,
                 extra_sections=[TOOL_FAILURE_GUIDANCE_PROMPT],
             )
@@ -693,6 +710,7 @@ class AgentLoop:
                     tool_calls=assistant_tool_calls or None,
                     finish_reason=response.finish_reason,
                     reasoning=response.reasoning_content,
+                    context_visible=not bool(assistant_tool_calls),
                     source=source,
                     title=title,
                     model=final_model,
@@ -707,7 +725,11 @@ class AgentLoop:
 
                 if not response.has_tool_calls:
                     final_text = response.content or ""
-                    final_finish_reason = response.finish_reason or "stop"
+                    if self._looks_like_raw_tool_call(final_text):
+                        final_text = RAW_TOOL_CALL_FALLBACK
+                        final_finish_reason = "invalid_tool_call_text"
+                    else:
+                        final_finish_reason = response.finish_reason or "stop"
                     break
 
                 if iterations >= resolved_max_tool_iterations:
@@ -719,10 +741,7 @@ class AgentLoop:
                         temperature=resolved_temperature,
                         thinking_enabled=thinking_enabled,
                     )
-                    final_text = finalized or (
-                        "Tool loop stopped after reaching the configured iteration limit, "
-                        "and no final answer was produced."
-                    )
+                    final_text = finalized or RAW_TOOL_CALL_FALLBACK
                     final_finish_reason = "max_tool_iterations_finalized" if finalized else "max_tool_iterations"
                     session_manager.append_message(
                         resolved_session_id,
@@ -877,17 +896,14 @@ class AgentLoop:
         temperature: float,
         thinking_enabled: bool | None,
     ) -> str:
-        final_messages = [
-            *messages,
-            {
-                "role": "system",
-                "content": (
-                    "The configured tool iteration budget is exhausted. Do not call tools. "
-                    "Produce the best final answer from the existing conversation and tool results. "
-                    "State uncertainty explicitly."
-                ),
-            },
-        ]
+        final_messages = AgentLoop._with_system_guidance(
+            messages,
+            (
+                "The configured tool iteration budget is exhausted. Do not call tools. "
+                "Produce the best final answer from the existing conversation and tool results. "
+                "State uncertainty explicitly."
+            ),
+        )
         kwargs: dict[str, Any] = {
             "messages": final_messages,
             "tools": None,
@@ -898,7 +914,27 @@ class AgentLoop:
         if thinking_enabled is not None:
             kwargs["thinking_enabled"] = thinking_enabled
         response = await provider.chat(**kwargs)
-        return (response.content or "").strip()
+        if response.has_tool_calls:
+            return ""
+        content = (response.content or "").strip()
+        if AgentLoop._looks_like_raw_tool_call(content):
+            return ""
+        return content
+
+    @staticmethod
+    def _looks_like_raw_tool_call(content: str | None) -> bool:
+        if not content:
+            return False
+        return bool(_RAW_TOOL_CALL_RE.match(content))
+
+    @staticmethod
+    def _with_system_guidance(messages: list[dict[str, Any]], guidance: str) -> list[dict[str, Any]]:
+        copied = [dict(message) for message in messages]
+        if copied and copied[0].get("role") == "system":
+            existing = str(copied[0].get("content") or "").strip()
+            copied[0]["content"] = "\n\n".join(part for part in (existing, guidance.strip()) if part)
+            return copied
+        return [{"role": "system", "content": guidance.strip()}, *copied]
 
     @staticmethod
     def _load_pinned_skill_contexts(skills_loader: Any, skill_names: list[str]) -> list[SkillContext]:
@@ -1133,3 +1169,49 @@ class AgentLoop:
     @staticmethod
     def _utc_now() -> str:
         return datetime.now(timezone.utc).isoformat()
+
+    @staticmethod
+    def _current_runtime_context() -> RuntimeContext:
+        utc_now = datetime.now(timezone.utc)
+        timezone_name = AgentLoop._configured_timezone_name()
+        local_now = datetime.now().astimezone()
+        rendered_timezone = local_now.tzname()
+
+        if timezone_name:
+            try:
+                local_now = utc_now.astimezone(ZoneInfo(timezone_name))
+                rendered_timezone = timezone_name
+            except ZoneInfoNotFoundError:
+                rendered_timezone = local_now.tzname() or timezone_name
+
+        return RuntimeContext(
+            utc_datetime=utc_now.isoformat(),
+            local_datetime=local_now.isoformat(),
+            timezone=rendered_timezone,
+            utc_offset=AgentLoop._format_utc_offset(local_now),
+        )
+
+    @staticmethod
+    def _configured_timezone_name() -> str | None:
+        for value in (os.getenv("BEAVER_RUNTIME_TIMEZONE"), os.getenv("TZ")):
+            cleaned = (value or "").strip()
+            if cleaned:
+                return cleaned
+
+        try:
+            timezone_file = "/etc/timezone"
+            if os.path.exists(timezone_file):
+                with open(timezone_file, encoding="utf-8") as file:
+                    cleaned = file.read().strip()
+                if cleaned:
+                    return cleaned
+        except OSError:
+            return None
+        return None
+
+    @staticmethod
+    def _format_utc_offset(value: datetime) -> str | None:
+        raw = value.strftime("%z")
+        if not raw:
+            return None
+        return f"{raw[:3]}:{raw[3:]}"

app-instance/backend/beaver/engine/providers/litellm.py

@@ -119,13 +119,23 @@ class LiteLLMProvider(LLMProvider):
     @staticmethod
     def _sanitize_messages(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
         sanitized = []
+        system_contents: list[str] = []
         for message in messages:
             clean = {key: value for key, value in message.items() if key in _ALLOWED_MSG_KEYS}
+            if clean.get("role") == "system":
+                content = clean.get("content")
+                if isinstance(content, str) and content.strip():
+                    system_contents.append(content.strip())
+                elif content is not None:
+                    system_contents.append(str(content))
+                continue
             if clean.get("role") == "assistant" and "content" not in clean:
                 clean["content"] = None
             if isinstance(clean.get("tool_calls"), list):
                 clean["tool_calls"] = LiteLLMProvider._sanitize_tool_calls(clean["tool_calls"])
             sanitized.append(clean)
+        if system_contents:
+            sanitized.insert(0, {"role": "system", "content": "\n\n".join(system_contents)})
         return sanitized
 
     @staticmethod

app-instance/backend/beaver/engine/session/models.py

@@ -84,8 +84,10 @@ class MessageRecord:
                 payload["task_id"] = self.event_payload.get("task_id")
             if self.event_payload.get("task_status"):
                 payload["task_status"] = self.event_payload.get("task_status")
-            if self.event_payload.get("validation_status"):
-                payload["validation_status"] = self.event_payload.get("validation_status")
+            if self.event_payload.get("evidence_status"):
+                payload["evidence_status"] = self.event_payload.get("evidence_status")
+            if self.event_payload.get("acceptance_state"):
+                payload["acceptance_state"] = self.event_payload.get("acceptance_state")
             if self.event_payload.get("feedback_state"):
                 payload["feedback_state"] = self.event_payload.get("feedback_state")
             if self.event_payload.get("feedback_error"):

app-instance/backend/beaver/foundation/config/loader.py

@@ -86,6 +86,18 @@ def _parse_agent_defaults(data: dict[str, Any]) -> AgentDefaultsConfig:
         model=_string(defaults.get("model") or data.get("model")),
         provider=_string(defaults.get("provider") or data.get("provider")),
         embedding_model=_string(defaults.get("embeddingModel") or defaults.get("embedding_model") or data.get("embeddingModel")),
+        max_context_messages=_int(
+            defaults.get("maxContextMessages")
+            or defaults.get("max_context_messages")
+            or data.get("maxContextMessages")
+            or data.get("max_context_messages")
+        ),
+        max_tool_iterations=_int(
+            defaults.get("maxToolIterations")
+            or defaults.get("max_tool_iterations")
+            or data.get("maxToolIterations")
+            or data.get("max_tool_iterations")
+        ),
     )
 
 
@@ -217,6 +229,13 @@ def _float(value: Any) -> float | None:
     return float(value)
 
 
+def _int(value: Any) -> int | None:
+    parsed = _float(value)
+    if parsed is None:
+        return None
+    return int(parsed)
+
+
 def _bool(value: Any, *, default: bool) -> bool:
     if isinstance(value, bool):
         return value

app-instance/backend/beaver/foundation/config/schema.py

@@ -25,6 +25,8 @@ class AgentDefaultsConfig:
     model: str | None = None
     provider: str | None = None
     embedding_model: str | None = None
+    max_context_messages: int | None = None
+    max_tool_iterations: int | None = None
 
 
 @dataclass(slots=True)

app-instance/backend/beaver/interfaces/web/app.py

@@ -44,6 +44,8 @@ from .files import (
     workspace_file_path,
 )
 from .schemas import (
+    WebChatAcceptanceRequest,
+    WebChatAcceptanceResponse,
     WebChatFeedbackRequest,
     WebChatFeedbackResponse,
     WebChatRequest,
@@ -155,6 +157,13 @@ except ModuleNotFoundError:  # pragma: no cover - fallback for skeleton-only env
             return decorator
 
 
+RAW_TOOL_CALL_DISPLAY_FALLBACK = (
+    "The run reached the configured tool-call limit before producing a reliable final answer. "
+    "The model attempted another tool call instead of answering, so the raw tool call was suppressed. "
+    "Please request a revision to continue the task."
+)
+
+
 @asynccontextmanager
 async def _app_lifespan(
     app: FastAPI,
@@ -365,6 +374,7 @@ def create_app(
             "workspace_exists": loaded.workspace.exists(),
             "model": config.default_model or agent_service.profile.default_model,
             "max_tokens": agent_service.profile.max_tokens,
+            "max_context_messages": agent_service.profile.max_context_messages,
             "temperature": agent_service.profile.temperature,
             "max_tool_iterations": agent_service.profile.max_tool_iterations,
             "providers": providers_status,
@@ -1719,7 +1729,8 @@ def create_app(
                 usage=result.usage,
                 task_id=result.task_id,
                 task_status=result.task_status,
-                validation_result=result.validation_result,
+                evidence_status="recorded" if result.task_id else None,
+                validation_result=None,
             )
 
         fallback_target = _model_dump(payload.fallback_target)
@@ -1769,7 +1780,8 @@ def create_app(
             usage=result.usage,
             task_id=result.task_id,
             task_status=result.task_status,
-            validation_result=result.validation_result,
+            evidence_status="recorded" if result.task_id else None,
+            validation_result=None,
         )
 
     @app.websocket("/ws/{session_id:path}")
@@ -1882,6 +1894,30 @@ def create_app(
                 }
             )
 
+    @app.post(
+        "/api/chat/acceptance",
+        response_model=WebChatAcceptanceResponse,
+        responses={
+            400: {"model": WebErrorResponse},
+            404: {"model": WebErrorResponse},
+        },
+    )
+    async def chat_acceptance(request: Request, payload: WebChatAcceptanceRequest) -> WebChatAcceptanceResponse:
+        agent_service = get_agent_service(request)
+        try:
+            result = await agent_service.submit_acceptance(
+                session_id=payload.session_id,
+                run_id=payload.run_id,
+                acceptance_type=payload.acceptance_type,
+                comment=payload.comment,
+            )
+        except ValueError as exc:
+            detail = str(exc)
+            status_code = 404 if "No internal task" in detail else 400
+            raise HTTPException(status_code=status_code, detail=detail) from exc
+
+        return WebChatAcceptanceResponse(**result)
+
     @app.post(
         "/api/chat/feedback",
         response_model=WebChatFeedbackResponse,
@@ -1893,10 +1929,10 @@ def create_app(
     async def chat_feedback(request: Request, payload: WebChatFeedbackRequest) -> WebChatFeedbackResponse:
         agent_service = get_agent_service(request)
         try:
-            result = await agent_service.submit_feedback(
+            result = await agent_service.submit_acceptance(
                 session_id=payload.session_id,
                 run_id=payload.run_id,
-                feedback_type=payload.feedback_type,
+                acceptance_type=payload.feedback_type,
                 comment=payload.comment,
             )
         except ValueError as exc:
@@ -1915,15 +1951,21 @@ def _session_detail(session_manager: Any, session_id: str, session: dict[str, An
         role = event.get("role")
         if role not in {"user", "assistant"}:
             continue
+        content = event.get("content") or ""
+        comparable_content = str(content).replace("\u200b", "").replace("\u200c", "").replace("\u200d", "").replace("\ufeff", "")
+        if role == "assistant" and not comparable_content.strip():
+            continue
+        content = _sanitize_user_visible_assistant_content(role=role, content=content)
         messages.append(
             {
                 "role": role,
-                "content": event.get("content") or "",
+                "content": content,
                 "timestamp": _iso_from_timestamp(event.get("timestamp")),
                 "run_id": event.get("run_id"),
                 "task_id": event.get("task_id"),
                 "task_status": event.get("task_status"),
-                "validation_status": event.get("validation_status"),
+                "evidence_status": event.get("evidence_status"),
+                "acceptance_state": event.get("acceptance_state"),
                 "feedback_state": event.get("feedback_state"),
                 "feedback_error": event.get("feedback_error"),
                 "message_type": event.get("message_type"),
@@ -2142,6 +2184,7 @@ def _task_run_views(task: Any, events: list[Any], session_manager: Any, run_memo
             content = (record.content or "").strip()
             if not content:
                 continue
+            content = _sanitize_user_visible_assistant_content(role=record.role, content=content)
             messages.append(
                 {
                     "role": record.role,
@@ -2150,7 +2193,6 @@ def _task_run_views(task: Any, events: list[Any], session_manager: Any, run_memo
                     "tool_name": record.tool_name,
                 }
             )
-        validation = run_record.validation_result if run_record is not None else None
         views.append(
             {
                 "run_id": run_id,
@@ -2163,7 +2205,8 @@ def _task_run_views(task: Any, events: list[Any], session_manager: Any, run_memo
                 "attempt_index": run_record.attempt_index if run_record is not None else None,
                 "task_text": run_record.task_text if run_record is not None else "",
                 "messages": messages,
-                "validation_result": validation,
+                "evidence_status": "recorded",
+                "validation_result": None,
             }
         )
     return views
@@ -2428,12 +2471,6 @@ def _model_dump(value: Any) -> dict[str, Any] | None:
     return dict(value)
 
 
-def _validation_status(validation_result: dict[str, Any] | None) -> str:
-    if validation_result is None:
-        return "unknown"
-    return "passed" if validation_result.get("accepted") is True else "failed"
-
-
 def _websocket_input_metadata(payload: dict[str, Any]) -> dict[str, Any]:
     metadata = payload.get("metadata") if isinstance(payload.get("metadata"), dict) else {}
     result: dict[str, Any] = dict(metadata)
@@ -2467,13 +2504,15 @@ def _int_or_none(value: Any) -> int | None:
 
 
 def _websocket_message_payload(result: Any, *, input_payload: dict[str, Any]) -> dict[str, Any]:
-    validation_result = getattr(result, "validation_result", None)
     task_id = getattr(result, "task_id", None)
     task_status = getattr(result, "task_status", None)
     return {
         "type": "message",
         "role": "assistant",
-        "content": getattr(result, "output_text", "") or "",
+        "content": _sanitize_user_visible_assistant_content(
+            role="assistant",
+            content=getattr(result, "output_text", "") or "",
+        ),
         "session_id": getattr(result, "session_id", None),
         "run_id": getattr(result, "run_id", None),
         "finish_reason": getattr(result, "finish_reason", None),
@@ -2483,17 +2522,39 @@ def _websocket_message_payload(result: Any, *, input_payload: dict[str, Any]) ->
         "usage": dict(getattr(result, "usage", {}) or {}),
         "task_id": task_id,
         "task_status": task_status,
-        "validation_result": validation_result,
-        "validation_status": _validation_status(validation_result),
+        "evidence_status": "recorded" if task_id else None,
+        "validation_result": None,
         "metadata": {
             "task_id": task_id,
             "task_status": task_status,
-            "validation_result": validation_result,
+            "evidence_status": "recorded" if task_id else None,
             "input_metadata": _websocket_input_metadata(input_payload),
         },
     }
 
 
+def _sanitize_user_visible_assistant_content(*, role: str, content: str) -> str:
+    if role != "assistant":
+        return content
+    if _looks_like_raw_tool_call(content):
+        return RAW_TOOL_CALL_DISPLAY_FALLBACK
+    return content
+
+
+def _looks_like_raw_tool_call(content: str | None) -> bool:
+    if not content:
+        return False
+    stripped = content.strip()
+    lowered = stripped.lower()
+    return (
+        lowered.startswith("<tool_call")
+        and lowered.endswith("</tool_call>")
+    ) or (
+        lowered.startswith("<function=")
+        and lowered.endswith("</function>")
+    )
+
+
 def _provider_enabled(provider_name: str, provider_cfg: Any) -> bool:
     if provider_cfg is None or provider_name == "custom":
         return False
@@ -2980,6 +3041,7 @@ def _write_config_json(path: Path, data: dict[str, Any]) -> None:
 def _reload_agent_config(agent_service: AgentService, config_path: Path) -> None:
     config = load_config(config_path=config_path)
     agent_service.loader.config = config
+    agent_service._apply_configured_profile_defaults()  # noqa: SLF001
     loop = getattr(agent_service, "_loop", None)
     loaded = getattr(loop, "loaded", None) if loop is not None else None
     if loaded is not None:

app-instance/backend/beaver/interfaces/web/schemas/__init__.py

@@ -1,6 +1,8 @@
 """Web request and response schemas."""
 
 from .chat import (
+    WebChatAcceptanceRequest,
+    WebChatAcceptanceResponse,
     WebChatFeedbackRequest,
     WebChatFeedbackResponse,
     WebChatRequest,
@@ -13,6 +15,8 @@ from .chat import (
 )
 
 __all__ = [
+    "WebChatAcceptanceRequest",
+    "WebChatAcceptanceResponse",
     "WebChatFeedbackRequest",
     "WebChatFeedbackResponse",
     "WebChatRequest",

app-instance/backend/beaver/interfaces/web/schemas/chat.py

@@ -82,11 +82,34 @@ class WebChatResponse(BaseModel):
     usage: dict[str, Any] = Field(default_factory=dict)
     task_id: str | None = None
     task_status: str | None = None
+    evidence_status: str | None = None
+    acceptance_state: str | None = None
     validation_result: dict[str, Any] | None = None
 
 
+class WebChatAcceptanceRequest(BaseModel):
+    """User acceptance on the latest assistant result in chat."""
+
+    session_id: str
+    run_id: str
+    acceptance_type: str
+    comment: str | None = None
+
+
+class WebChatAcceptanceResponse(BaseModel):
+    """Acceptance recording result."""
+
+    session_id: str
+    run_id: str
+    task_id: str
+    task_status: str
+    acceptance_type: str
+    feedback_type: str
+    learning_candidates: list[dict[str, Any]] = Field(default_factory=list)
+
+
 class WebChatFeedbackRequest(BaseModel):
-    """Feedback on the latest assistant result in chat."""
+    """Backward-compatible feedback payload."""
 
     session_id: str
     run_id: str
@@ -94,15 +117,8 @@ class WebChatFeedbackRequest(BaseModel):
     comment: str | None = None
 
 
-class WebChatFeedbackResponse(BaseModel):
-    """Feedback recording result."""
-
-    session_id: str
-    run_id: str
-    task_id: str
-    task_status: str
-    feedback_type: str
-    learning_candidates: list[dict[str, Any]] = Field(default_factory=list)
+class WebChatFeedbackResponse(WebChatAcceptanceResponse):
+    """Backward-compatible feedback response."""
 
 
 class WebProviderConfigRequest(BaseModel):

app-instance/backend/beaver/services/agent_service.py

@@ -29,9 +29,9 @@ from beaver.tasks import (
     TaskEvidencePacket,
     TaskExecutionPlan,
     TaskRecord,
-    ValidationResult,
     render_task_evidence,
 )
+from beaver.tasks.service import normalize_acceptance_type
 
 
 NOTIFICATION_SESSION_ID = "notify:default:scheduled"
@@ -60,11 +60,19 @@ class AgentService:
     ) -> None:
         self.profile = profile or AgentProfile()
         self.loader = loader or EngineLoader(workspace=workspace, config_path=config_path)
+        self._apply_configured_profile_defaults()
         self._loop: AgentLoop | None = None
         self._run_task: asyncio.Task[None] | None = None
         self._main_agent_router = MainAgentRouter()
         self._runtime_services: dict[str, Any] = {}
 
+    def _apply_configured_profile_defaults(self) -> None:
+        defaults = self.loader.config.agents_defaults
+        if defaults.max_context_messages is not None:
+            self.profile.max_context_messages = max(1, defaults.max_context_messages)
+        if defaults.max_tool_iterations is not None:
+            self.profile.max_tool_iterations = max(0, defaults.max_tool_iterations)
+
     def create_loop(self) -> AgentLoop:
         """创建并缓存当前 service 使用的 AgentLoop。"""
 
@@ -232,7 +240,7 @@ class AgentService:
 
         Scheduled jobs are product-level Tasks, not hidden one-off agent turns.
         This entry bypasses the main-agent classifier and forces Task mode so
-        every trigger produces a TaskRecord, validation, feedback state, and a
+        every trigger produces a TaskRecord, evidence, acceptance state, and a
         run_id that the scheduled-task history can link to.
         """
 
@@ -280,9 +288,9 @@ class AgentService:
             result.run_id,
             {
                 "message_type": "scheduled_reply",
-                "scheduled_job_id": job.id,
-                "scheduled_run_id": run.scheduled_run_id,
-                "cron_job_name": job.name,
+                "scheduled_job_id": cron_job_id,
+                "scheduled_run_id": scheduled_run_id,
+                "cron_job_name": cron_job_name,
                 "mode": "notification",
             },
         )
@@ -403,15 +411,15 @@ class AgentService:
             },
         )
 
-    async def submit_feedback(
+    async def submit_acceptance(
         self,
         *,
         session_id: str,
         run_id: str,
-        feedback_type: str,
+        acceptance_type: str,
         comment: str | None = None,
     ) -> dict[str, Any]:
-        """Record chat feedback for the internal task linked to a run."""
+        """Record user acceptance for the internal task linked to a run."""
 
         loaded = self.create_loop().boot()
         task_service = self._require_loaded(loaded, "task_service")
@@ -419,32 +427,31 @@ class AgentService:
         if task is None or task.session_id != session_id:
             raise ValueError(f"No internal task found for run_id={run_id!r}")
 
-        normalized = feedback_type.strip().lower()
-        if normalized not in {"satisfied", "revise", "abandon"}:
-            raise ValueError("feedback_type must be one of: satisfied, revise, abandon")
+        normalized = normalize_acceptance_type(acceptance_type)
+        legacy_feedback_type = "satisfied" if normalized == "accept" else normalized
 
         already_recorded = any(
-            item.get("run_id") == run_id and item.get("feedback_type") == normalized
+            item.get("run_id") == run_id and item.get("acceptance_type") == normalized
             for item in task.feedback
         )
-        conflicting_feedback = next(
+        conflicting_acceptance = next(
             (
                 item
                 for item in task.feedback
-                if item.get("run_id") == run_id and item.get("feedback_type") != normalized
+                if item.get("run_id") == run_id and item.get("acceptance_type") != normalized
             ),
             None,
         )
-        if conflicting_feedback is not None:
+        if conflicting_acceptance is not None:
             raise ValueError(
-                f"Feedback for run_id={run_id!r} was already recorded as "
-                f"{conflicting_feedback.get('feedback_type')!r}"
+                f"Acceptance for run_id={run_id!r} was already recorded as "
+                f"{conflicting_acceptance.get('acceptance_type')!r}"
             )
         if task.status in {"closed", "abandoned"} and not already_recorded:
             raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
-        updated = task if already_recorded else task_service.add_feedback(
+        updated = task if already_recorded else task_service.add_acceptance(
             task.task_id,
-            feedback_type=normalized,
+            acceptance_type=normalized,
             comment=comment,
             run_id=run_id,
         )
@@ -455,7 +462,8 @@ class AgentService:
             {
                 "task_id": updated.task_id,
                 "task_status": updated.status,
-                "feedback_state": normalized,
+                "acceptance_state": normalized,
+                "feedback_state": legacy_feedback_type,
             },
         )
         if not already_recorded:
@@ -463,10 +471,11 @@ class AgentService:
                 session_id,
                 run_id=run_id,
                 role="system",
-                event_type="task_feedback_recorded",
+                event_type="task_acceptance_recorded",
                 event_payload={
                     "task_id": task.task_id,
-                    "feedback_type": normalized,
+                    "acceptance_type": normalized,
+                    "feedback_type": legacy_feedback_type,
                     "comment": comment,
                     "task_status": updated.status,
                 },
@@ -475,35 +484,36 @@ class AgentService:
             )
 
         generated_candidates = []
-        validation = ValidationResult.from_dict(updated.validation_result)
         if not already_recorded:
             run_memory_store = self._require_loaded(loaded, "run_memory_store")
-            feedback_payload = {
-                "feedback_type": normalized,
+            acceptance_payload = {
+                "acceptance_type": normalized,
+                "feedback_type": legacy_feedback_type,
                 "comment": comment or "",
                 "task_status": updated.status,
+                "final_accepted_run_id": updated.metadata.get("final_accepted_run_id"),
             }
             run_memory_store.update_run_record(
                 run_id,
-                success=normalized == "satisfied",
-                feedback=feedback_payload,
+                success=normalized == "accept",
+                feedback=acceptance_payload,
             )
             run_memory_store.update_skill_effects_for_run(
                 run_id,
-                success=normalized == "satisfied",
-                feedback_score=self._feedback_score_for_learning(normalized, validation),
+                success=normalized == "accept",
+                feedback_score=self._acceptance_score_for_learning(normalized),
                 notes=(comment or normalized).strip(),
             )
             skill_learning_service = self._require_loaded(loaded, "skill_learning_service")
             skill_learning_service.rescore_skill_versions()
         if already_recorded:
             generated_candidates = []
-        elif normalized == "satisfied" and validation is not None and validation.accepted:
+        elif normalized == "accept":
             generated_candidates = [
                 item.to_dict()
                 for item in skill_learning_service.build_learning_candidates_for_task(
                     updated.task_id,
-                    trigger_run_id=run_id,
+                    final_accepted_run_id=run_id,
                 )
             ]
         elif normalized == "abandon":
@@ -514,7 +524,8 @@ class AgentService:
                 event_type="task_failure_evidence_recorded",
                 event_payload={
                     "task_id": updated.task_id,
-                    "feedback_type": normalized,
+                    "acceptance_type": normalized,
+                    "feedback_type": legacy_feedback_type,
                     "comment": comment or "",
                     "task_status": updated.status,
                     "durable_memory_written": False,
@@ -528,10 +539,28 @@ class AgentService:
             "run_id": run_id,
             "task_id": updated.task_id,
             "task_status": updated.status,
-            "feedback_type": normalized,
+            "acceptance_type": normalized,
+            "feedback_type": legacy_feedback_type,
             "learning_candidates": generated_candidates,
         }
 
+    async def submit_feedback(
+        self,
+        *,
+        session_id: str,
+        run_id: str,
+        feedback_type: str,
+        comment: str | None = None,
+    ) -> dict[str, Any]:
+        """Backward-compatible wrapper for older clients."""
+
+        return await self.submit_acceptance(
+            session_id=session_id,
+            run_id=run_id,
+            acceptance_type=feedback_type,
+            comment=comment,
+        )
+
     async def _process_with_main_agent(
         self,
         message: str,
@@ -591,7 +620,7 @@ class AgentService:
             else active_task
         )
         if active_task is not None and decision.action == "revise_task" and task.task_id == active_task.task_id:
-            task = self._record_revision_feedback_for_task(
+            task = self._record_revision_acceptance_for_task(
                 loaded,
                 task=task,
                 session_id=session_id,
@@ -599,7 +628,7 @@ class AgentService:
             )
         return await self._run_task_mode(message, runner=runner, kwargs=kwargs, task=task)
 
-    def _record_revision_feedback_for_task(
+    def _record_revision_acceptance_for_task(
         self,
         loaded: Any,
         *,
@@ -607,9 +636,9 @@ class AgentService:
         session_id: str,
         comment: str,
     ) -> TaskRecord:
-        """Mark the latest feedback-eligible run as revised before continuing a task."""
+        """Mark the latest acceptance-eligible run as revised before continuing a task."""
 
-        if task.status not in {"awaiting_feedback", "needs_revision"}:
+        if task.status not in {"awaiting_acceptance", "needs_revision"}:
             return task
         run_id = next((item for item in reversed(task.run_ids) if item), None)
         if not run_id:
@@ -617,15 +646,15 @@ class AgentService:
 
         existing = next((item for item in task.feedback if item.get("run_id") == run_id), None)
         if existing is not None:
-            if existing.get("feedback_type") != "revise":
+            if existing.get("acceptance_type") != "revise":
                 return task
             updated = task
             already_recorded = True
         else:
             task_service = self._require_loaded(loaded, "task_service")
-            updated = task_service.add_feedback(
+            updated = task_service.add_acceptance(
                 task.task_id,
-                feedback_type="revise",
+                acceptance_type="revise",
                 comment=comment,
                 run_id=run_id,
             )
@@ -638,6 +667,7 @@ class AgentService:
             {
                 "task_id": updated.task_id,
                 "task_status": updated.status,
+                "acceptance_state": "revise",
                 "feedback_state": "revise",
             },
         )
@@ -648,9 +678,10 @@ class AgentService:
             session_id,
             run_id=run_id,
             role="system",
-            event_type="task_feedback_recorded",
+            event_type="task_acceptance_recorded",
             event_payload={
                 "task_id": updated.task_id,
+                "acceptance_type": "revise",
                 "feedback_type": "revise",
                 "comment": comment,
                 "task_status": updated.status,
@@ -659,12 +690,12 @@ class AgentService:
             content=comment,
             context_visible=False,
         )
-        validation = ValidationResult.from_dict(updated.validation_result)
         run_memory_store = self._require_loaded(loaded, "run_memory_store")
         run_memory_store.update_run_record(
             run_id,
             success=False,
             feedback={
+                "acceptance_type": "revise",
                 "feedback_type": "revise",
                 "comment": comment,
                 "task_status": updated.status,
@@ -673,7 +704,7 @@ class AgentService:
         run_memory_store.update_skill_effects_for_run(
             run_id,
             success=False,
-            feedback_score=self._feedback_score_for_learning("revise", validation),
+            feedback_score=self._acceptance_score_for_learning("revise"),
             notes=comment.strip() or "revise",
         )
         skill_learning_service = self._require_loaded(loaded, "skill_learning_service")
@@ -690,236 +721,185 @@ class AgentService:
     ) -> AgentRunResult:
         loaded = self.create_loop().boot()
         task_service = self._require_loaded(loaded, "task_service")
-        validation_service = self._require_loaded(loaded, "validation_service")
         task_execution_planner = self._require_loaded(loaded, "task_execution_planner")
         session_manager = self._require_loaded(loaded, "session_manager")
-        run_memory_store = self._require_loaded(loaded, "run_memory_store")
 
-        last_result: AgentRunResult | None = None
-        latest_validation: ValidationResult | None = None
         base_execution_context = kwargs.get("execution_context")
         provider_bundle = kwargs.get("provider_bundle") or self._make_provider_bundle_for_task(loaded, kwargs)
         kwargs = dict(kwargs)
         team_provider_bundle_factory = kwargs.pop("team_provider_bundle_factory", None)
         kwargs["provider_bundle"] = provider_bundle
 
-        for attempt_index in (1, 2):
-            task_service.start_run(task.task_id, user_message=message, attempt_index=attempt_index)
-            plan = await task_execution_planner.plan(
+        attempt_index = int(task.metadata.get("latest_attempt_index") or 0) + 1
+        task_service.start_run(task.task_id, user_message=message, attempt_index=attempt_index)
+        plan = await task_execution_planner.plan(
+            task=task,
+            user_message=message,
+            attempt_index=attempt_index,
+            provider_bundle=provider_bundle,
+        )
+        self._append_task_observation(
+            session_manager,
+            task.session_id,
+            event_type="task_execution_planned",
+            payload={
+                "task_id": task.task_id,
+                "attempt_index": attempt_index,
+                **plan.to_event_payload(),
+            },
+        )
+        team_summaries: list[str] = []
+        team_execution_context = ""
+        team_result: TeamRunResult | None = None
+        if plan.is_team:
+            team_result, team_error = await self._run_team_for_task(
+                plan,
                 task=task,
-                user_message=message,
-                attempt_index=attempt_index,
-                latest_validation=latest_validation,
-                provider_bundle=provider_bundle,
+                parent_session_id=kwargs["session_id"],
+                provider_bundle_factory=team_provider_bundle_factory
+                or self._build_team_provider_bundle_factory(loaded, kwargs),
             )
-            self._append_task_observation(
-                session_manager,
-                task.session_id,
-                event_type="task_execution_planned",
-                payload={
-                    "task_id": task.task_id,
-                    "attempt_index": attempt_index,
-                    **plan.to_event_payload(),
-                },
-            )
-            team_summaries: list[str] = []
-            team_execution_context = ""
-            team_result: TeamRunResult | None = None
-            if plan.is_team:
-                team_result, team_error = await self._run_team_for_task(
-                    plan,
-                    task=task,
-                    parent_session_id=kwargs["session_id"],
-                    provider_bundle_factory=team_provider_bundle_factory
-                    or self._build_team_provider_bundle_factory(loaded, kwargs),
+            if team_result is not None:
+                team_summaries = [self._team_summary_for_validation(team_result)]
+                team_packet = TaskEvidencePacket(
+                    task_id=task.task_id,
+                    attempt_index=attempt_index,
+                    main_run=None,
+                    team_runs=self._team_run_evidence(team_result),
+                    team_node_results=list(team_result.node_results),
+                    final_output="",
+                )
+                team_execution_context = self._join_context(
+                    self._team_execution_context(plan, team_result),
+                    "Rendered team evidence:\n" + render_task_evidence(team_packet),
+                )
+                self._append_task_observation(
+                    session_manager,
+                    task.session_id,
+                    event_type="task_team_run_completed" if team_result.success else "task_team_run_failed",
+                    payload={
+                        "task_id": task.task_id,
+                        "attempt_index": attempt_index,
+                        "plan_mode": plan.mode,
+                        "strategy": plan.graph.strategy if plan.graph else None,
+                        "node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
+                        "team_run_ids": team_result.run_ids,
+                        "team_success": team_result.success,
+                        "node_results": self._team_node_results_for_event(plan, team_result),
+                        "reason": plan.reason,
+                        "error": None if team_result.success else "one or more team nodes failed",
+                    },
+                )
+            else:
+                team_summaries = [f"Team execution failed: {team_error}"]
+                team_execution_context = self._failed_team_execution_context(plan, team_error or "unknown error")
+                self._append_task_observation(
+                    session_manager,
+                    task.session_id,
+                    event_type="task_team_run_failed",
+                    payload={
+                        "task_id": task.task_id,
+                        "attempt_index": attempt_index,
+                        "plan_mode": plan.mode,
+                        "strategy": plan.graph.strategy if plan.graph else None,
+                        "node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
+                        "team_run_ids": [],
+                        "team_success": False,
+                        "reason": plan.reason,
+                        "error": team_error,
+                    },
                 )
-                if team_result is not None:
-                    team_summaries = [self._team_summary_for_validation(team_result)]
-                    team_packet = TaskEvidencePacket(
-                        task_id=task.task_id,
-                        attempt_index=attempt_index,
-                        main_run=None,
-                        team_runs=self._team_run_evidence(team_result),
-                        team_node_results=list(team_result.node_results),
-                        final_output="",
-                    )
-                    team_execution_context = self._join_context(
-                        self._team_execution_context(plan, team_result),
-                        "Rendered team evidence:\n" + render_task_evidence(team_packet),
-                    )
-                    self._append_task_observation(
-                        session_manager,
-                        task.session_id,
-                        event_type="task_team_run_completed" if team_result.success else "task_team_run_failed",
-                        payload={
-                            "task_id": task.task_id,
-                            "attempt_index": attempt_index,
-                            "plan_mode": plan.mode,
-                            "strategy": plan.graph.strategy if plan.graph else None,
-                            "node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
-                            "team_run_ids": team_result.run_ids,
-                            "team_success": team_result.success,
-                            "node_results": self._team_node_results_for_event(plan, team_result),
-                            "reason": plan.reason,
-                            "error": None if team_result.success else "one or more team nodes failed",
-                        },
-                    )
-                else:
-                    team_summaries = [f"Team execution failed: {team_error}"]
-                    team_execution_context = self._failed_team_execution_context(plan, team_error or "unknown error")
-                    self._append_task_observation(
-                        session_manager,
-                        task.session_id,
-                        event_type="task_team_run_failed",
-                        payload={
-                            "task_id": task.task_id,
-                            "attempt_index": attempt_index,
-                            "plan_mode": plan.mode,
-                            "strategy": plan.graph.strategy if plan.graph else None,
-                            "node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
-                            "team_run_ids": [],
-                            "team_success": False,
-                            "reason": plan.reason,
-                            "error": team_error,
-                        },
-                    )
 
-            attempt_kwargs = dict(kwargs)
-            attempt_kwargs.update(
-                {
-                    "task_id": task.task_id,
-                    "task_mode": True,
-                    "attempt_index": attempt_index,
-                    "allow_candidate_generation": False,
-                }
-            )
-            if attempt_index == 2 and latest_validation is not None:
-                revision_context = latest_validation.recommended_revision_prompt.strip()
-                if revision_context:
-                    attempt_kwargs["execution_context"] = self._join_context(
-                        base_execution_context,
-                        f"Task validation revision request:\n{revision_context}",
-                        team_execution_context,
-                    )
-            elif team_execution_context:
-                attempt_kwargs["execution_context"] = self._join_context(base_execution_context, team_execution_context)
-            if plan.is_team and team_execution_context:
-                attempt_kwargs["include_tools"] = False
-                attempt_kwargs["max_tool_iterations"] = 0
-            attempt_kwargs["skill_selection_context"] = self._build_skill_selection_context(
-                task=task,
-                user_message=message,
-                attempt_index=attempt_index,
-                latest_validation=latest_validation,
-                plan=plan,
-                team_summaries=team_summaries,
-            )
-
-            result = await runner(message, **attempt_kwargs)
-            last_result = result
-            self._append_task_observation(
-                session_manager,
-                task.session_id,
-                event_type="task_synthesis_completed",
-                payload={
-                    "task_id": task.task_id,
-                    "attempt_index": attempt_index,
-                    "main_run_id": result.run_id,
-                    "plan_mode": plan.mode,
-                    "strategy": plan.graph.strategy if plan.graph else None,
-                },
-            )
-            task = task_service.append_run(
-                task.task_id,
-                result.run_id,
-                skill_names=self._skill_names_for_run(loaded, result.run_id),
-            )
-            evidence_packet = self._build_task_evidence_packet(
-                session_manager=session_manager,
-                task=task,
-                attempt_index=attempt_index,
-                result=result,
-                team_result=team_result,
-            )
-            evidence_text = render_task_evidence(evidence_packet)
-            validation = await validation_service.validate_task_result(
-                task=task,
-                user_message=message,
-                final_output=result.output_text,
-                evidence_packet=evidence_packet,
-                evidence_text=evidence_text,
-                transcript_excerpt=self._run_excerpt(session_manager, result.session_id, result.run_id),
-                tool_summaries=self._tool_summaries(session_manager, result.session_id, result.run_id),
-                team_summaries=team_summaries,
-                provider_bundle=provider_bundle,
-            )
-            latest_validation = validation
-            has_usable_answer = bool(result.output_text.strip()) and (
-                "Tool loop stopped after reaching the configured iteration limit." not in result.output_text
-            )
-            task = task_service.record_validation(
-                task.task_id,
-                result.run_id,
-                validation,
-                final_attempt=(
-                    attempt_index == 2
-                    or validation.status in {"accepted", "insufficient_evidence", "validator_error"}
-                ),
-                has_usable_answer=has_usable_answer,
-            )
-            run_memory_store.update_run_record(result.run_id, validation_result=validation.to_dict())
-            session_manager.update_latest_assistant_event_payload(
-                result.session_id,
-                result.run_id,
-                {
-                    "task_id": task.task_id,
-                    "task_status": task.status,
-                    "validation_status": "passed" if validation.accepted else "failed",
-                },
-            )
-            validation_debug = {
-                "evidence_run_ids": [
-                    item.run_id for item in [evidence_packet.main_run, *evidence_packet.team_runs] if item is not None
-                ],
-                "evidence_session_ids": [
-                    item.session_id
-                    for item in [evidence_packet.main_run, *evidence_packet.team_runs]
-                    if item is not None
-                ],
-                "tool_result_count": sum(
-                    len(item.tool_results)
-                    for item in [evidence_packet.main_run, *evidence_packet.team_runs]
-                    if item is not None
-                ),
-                "evidence_length": len(evidence_text),
+        attempt_kwargs = dict(kwargs)
+        attempt_kwargs.update(
+            {
+                "task_id": task.task_id,
+                "task_mode": True,
+                "attempt_index": attempt_index,
+                "allow_candidate_generation": False,
             }
-            retry_scheduled = validation.status == "rejected" and attempt_index == 1
-            session_manager.append_message(
-                result.session_id,
-                run_id=result.run_id,
-                role="system",
-                event_type="task_validation_snapshotted",
-                event_payload={
-                    "task_id": task.task_id,
-                    "attempt_index": attempt_index,
-                    "validation_result": validation.to_dict(),
-                    "validation_debug": validation_debug,
-                    "retry_scheduled": retry_scheduled,
-                },
-                content=validation.recommended_revision_prompt or None,
-                context_visible=False,
-            )
-            if retry_scheduled:
-                session_manager.set_run_context_visible(result.session_id, result.run_id, False)
-            result.task_id = task.task_id
-            result.task_status = task.status
-            result.validation_result = validation.to_dict()
-            if not retry_scheduled:
-                return result
+        )
+        if team_execution_context:
+            attempt_kwargs["execution_context"] = self._join_context(base_execution_context, team_execution_context)
+        if plan.is_team and team_execution_context:
+            attempt_kwargs["include_tools"] = False
+            attempt_kwargs["max_tool_iterations"] = 0
+        attempt_kwargs["skill_selection_context"] = self._build_skill_selection_context(
+            task=task,
+            user_message=message,
+            attempt_index=attempt_index,
+            plan=plan,
+            team_summaries=team_summaries,
+        )
 
-        if last_result is None:  # pragma: no cover - defensive
-            raise RuntimeError("Task mode did not produce a run result")
-        return last_result
+        result = await runner(message, **attempt_kwargs)
+        self._append_task_observation(
+            session_manager,
+            task.session_id,
+            event_type="task_synthesis_completed",
+            payload={
+                "task_id": task.task_id,
+                "attempt_index": attempt_index,
+                "main_run_id": result.run_id,
+                "plan_mode": plan.mode,
+                "strategy": plan.graph.strategy if plan.graph else None,
+            },
+        )
+        task = task_service.append_run(
+            task.task_id,
+            result.run_id,
+            skill_names=self._skill_names_for_run(loaded, result.run_id),
+        )
+        evidence_packet = self._build_task_evidence_packet(
+            session_manager=session_manager,
+            task=task,
+            attempt_index=attempt_index,
+            result=result,
+            team_result=team_result,
+        )
+        evidence_text = render_task_evidence(evidence_packet)
+        evidence_debug = {
+            "evidence_run_ids": [
+                item.run_id for item in [evidence_packet.main_run, *evidence_packet.team_runs] if item is not None
+            ],
+            "evidence_session_ids": [
+                item.session_id
+                for item in [evidence_packet.main_run, *evidence_packet.team_runs]
+                if item is not None
+            ],
+            "tool_result_count": sum(
+                len(item.tool_results)
+                for item in [evidence_packet.main_run, *evidence_packet.team_runs]
+                if item is not None
+            ),
+            "evidence_length": len(evidence_text),
+        }
+        session_manager.update_latest_assistant_event_payload(
+            result.session_id,
+            result.run_id,
+            {
+                "task_id": task.task_id,
+                "task_status": task.status,
+                "evidence_status": "recorded",
+            },
+        )
+        session_manager.append_message(
+            result.session_id,
+            run_id=result.run_id,
+            role="system",
+            event_type="task_evidence_recorded",
+            event_payload={
+                "task_id": task.task_id,
+                "attempt_index": attempt_index,
+                "evidence_debug": evidence_debug,
+            },
+            content=None,
+            context_visible=False,
+        )
+        result.task_id = task.task_id
+        result.task_status = task.status
+        result.validation_result = None
+        return result
 
     async def _run_team_for_task(
         self,
@@ -986,12 +966,10 @@ class AgentService:
         return []
 
     @staticmethod
-    def _feedback_score_for_learning(feedback_type: str, validation: ValidationResult | None) -> float:
-        if feedback_type == "satisfied":
-            if validation is not None:
-                return max(0.0, min(1.0, float(validation.score)))
+    def _acceptance_score_for_learning(acceptance_type: str) -> float:
+        if acceptance_type == "accept":
             return 1.0
-        if feedback_type == "revise":
+        if acceptance_type == "revise":
             return 0.5
         return 0.0
 
@@ -1001,12 +979,11 @@ class AgentService:
         task: TaskRecord,
         user_message: str,
         attempt_index: int,
-        latest_validation: ValidationResult | None = None,
         plan: TaskExecutionPlan | None = None,
         team_summaries: list[str] | None = None,
     ) -> str:
         phase = f"attempt_{attempt_index}"
-        if latest_validation is not None:
+        if task.feedback and task.feedback[-1].get("acceptance_type") == "revise":
             phase = f"revision_attempt_{attempt_index}"
         elif plan is not None and plan.is_team:
             phase = f"team_synthesis_attempt_{attempt_index}"
@@ -1027,24 +1004,14 @@ class AgentService:
             )
         else:
             sections.append("Previously activated skills:\nNone")
-        if latest_validation is not None:
-            validation_lines = [
-                f"accepted: {latest_validation.accepted}",
-                f"score: {latest_validation.score}",
-            ]
-            if latest_validation.issues:
-                validation_lines.append("issues:\n" + "\n".join(f"- {item}" for item in latest_validation.issues))
-            if latest_validation.missing_requirements:
-                validation_lines.append(
-                    "missing requirements:\n"
-                    + "\n".join(f"- {item}" for item in latest_validation.missing_requirements)
-                )
-            if latest_validation.recommended_revision_prompt:
-                validation_lines.append(
-                    "recommended revision:\n"
-                    + latest_validation.recommended_revision_prompt
-                )
-            sections.append("Validation feedback:\n" + "\n".join(validation_lines))
+        if task.feedback:
+            history_lines = []
+            for item in task.feedback[-5:]:
+                kind = item.get("acceptance_type") or item.get("feedback_type")
+                comment = item.get("comment") or ""
+                run_id = item.get("run_id") or ""
+                history_lines.append(f"- {kind} run={run_id}: {comment}".strip())
+            sections.append("Task acceptance history:\n" + "\n".join(history_lines))
         if plan is not None:
             plan_lines = [
                 f"mode: {plan.mode}",
@@ -1313,7 +1280,8 @@ class AgentService:
                 "inbound_metadata": dict(inbound.metadata),
                 "task_id": getattr(result, "task_id", None),
                 "task_status": getattr(result, "task_status", None),
-                "validation_result": getattr(result, "validation_result", None),
+                "evidence_status": "recorded" if getattr(result, "task_id", None) else None,
+                "validation_result": None,
             },
         )
 

app-instance/backend/beaver/services/process_service.py

@@ -235,26 +235,45 @@ class SessionProcessProjector:
                         metadata=dict(payload),
                     )
 
-            elif record.event_type == "task_validation_snapshotted":
-                validation = payload.get("validation_result") if isinstance(payload.get("validation_result"), dict) else {}
-                accepted = bool(validation.get("accepted"))
-                root["status"] = "done" if accepted or attempt_index == 2 else "waiting"
-                root["finished_at"] = created_at if root["status"] == "done" else None
+            elif record.event_type == "task_evidence_recorded":
+                root["status"] = "waiting"
+                root["finished_at"] = None
                 add_event(
-                    event_id=_event_id(record, "validation"),
+                    event_id=_event_id(record, "evidence"),
                     run_id=record.run_id or root_run_id,
                     parent_run_id=root_run_id if record.run_id else None,
                     kind="run_status",
                     actor_type="system",
-                    actor_id="validator",
-                    actor_name="Validator",
-                    text=(
-                        f"Validation {'passed' if accepted else 'failed'} "
-                        f"(score={validation.get('score')})."
-                        + (" Retry scheduled." if payload.get("retry_scheduled") else "")
-                    ),
+                    actor_id="evidence-recorder",
+                    actor_name="Evidence",
+                    text="Task evidence was recorded; waiting for user acceptance.",
                     created_at=created_at,
-                    status="done" if accepted else "error",
+                    status="done",
+                    metadata=dict(payload),
+                )
+
+            elif record.event_type == "task_acceptance_recorded":
+                acceptance_type = str(payload.get("acceptance_type") or payload.get("feedback_type") or "")
+                if acceptance_type == "accept":
+                    root["status"] = "done"
+                    root["finished_at"] = created_at
+                elif acceptance_type == "abandon":
+                    root["status"] = "cancelled"
+                    root["finished_at"] = created_at
+                else:
+                    root["status"] = "waiting"
+                    root["finished_at"] = None
+                add_event(
+                    event_id=_event_id(record, "acceptance"),
+                    run_id=record.run_id or root_run_id,
+                    parent_run_id=root_run_id if record.run_id else None,
+                    kind="run_status",
+                    actor_type="user",
+                    actor_id="user-acceptance",
+                    actor_name="User Acceptance",
+                    text=f"User acceptance recorded: {acceptance_type or 'unknown'}.",
+                    created_at=created_at,
+                    status="done",
                     metadata=dict(payload),
                 )
 

app-instance/backend/beaver/skills/learning/service.py

@@ -69,15 +69,24 @@ class SkillLearningService:
                 existing_ids.add(candidate.candidate_id)
         return candidates
 
-    def build_learning_candidates_for_task(self, task_id: str, *, trigger_run_id: str) -> list[SkillLearningCandidate]:
-        """Build candidates scoped to a single validated and satisfied Task run."""
+    def build_learning_candidates_for_task(
+        self,
+        task_id: str,
+        *,
+        final_accepted_run_id: str | None = None,
+        trigger_run_id: str | None = None,
+    ) -> list[SkillLearningCandidate]:
+        """Build candidates from a user-accepted Task and all of its runs."""
 
+        final_accepted_run_id = final_accepted_run_id or trigger_run_id
+        if not final_accepted_run_id:
+            return []
         runs = [record for record in self.run_store.list_runs() if record.task_id == task_id]
-        trigger_run = next((record for record in runs if record.run_id == trigger_run_id), None)
-        if trigger_run is None or not self._is_confirmed_positive_run(trigger_run):
+        final_run = next((record for record in runs if record.run_id == final_accepted_run_id), None)
+        if final_run is None or not self._is_task_accepted_run(final_run):
             return []
 
-        source_runs = [record for record in runs if self._is_confirmed_positive_run(record)]
+        source_runs = sorted(runs, key=lambda item: (item.started_at, item.run_id))
         if not source_runs:
             return []
 
@@ -100,11 +109,16 @@ class SkillLearningService:
                     source_session_ids=source_session_ids,
                     related_skill_names=[],
                     reason=f"Task {task_id} completed successfully without a published skill; consider extracting reusable guidance.",
-                    evidence={"task_id": task_id, "trigger_run_id": trigger_run_id, "theme": self._task_theme(trigger_run.task_text)},
+                    evidence={
+                        "task_id": task_id,
+                        "final_accepted_run_id": final_accepted_run_id,
+                        "source_run_ids": source_run_ids,
+                        "theme": self._task_theme(final_run.task_text),
+                    },
                     status="open",
                     priority=1,
                     confidence=0.8,
-                    trigger_reason="validation_accepted_and_user_satisfied",
+                    trigger_reason="task_accepted",
                 )
             )
         else:
@@ -137,13 +151,14 @@ class SkillLearningService:
                         ),
                         evidence={
                             "task_id": task_id,
-                            "trigger_run_id": trigger_run_id,
+                            "final_accepted_run_id": final_accepted_run_id,
+                            "source_run_ids": source_run_ids,
                             "skill_version": receipt.skill_version,
                         },
                         status="open",
                         priority=1,
                         confidence=0.7,
-                        trigger_reason="validation_accepted_and_user_satisfied",
+                        trigger_reason="task_accepted",
                     )
                 )
 
@@ -269,7 +284,7 @@ class SkillLearningService:
             groups.setdefault(key, []).append(record)
         candidates: list[SkillLearningCandidate] = []
         for theme, runs in groups.items():
-            successful = [record for record in runs if self._is_confirmed_positive_run(record)]
+            successful = [record for record in runs if self._is_task_accepted_run(record)]
             if len(successful) < 2:
                 continue
             if any(record.activated_skills for record in successful):
@@ -290,7 +305,7 @@ class SkillLearningService:
     def _build_merge_candidates(self) -> list[SkillLearningCandidate]:
         pair_counts: dict[tuple[str, str], list[RunRecord]] = {}
         for record in self.run_store.list_runs():
-            if not self._is_confirmed_positive_run(record):
+            if not self._is_task_accepted_run(record):
                 continue
             unique = sorted({receipt.skill_name for receipt in record.activated_skills})
             for pair in combinations(unique, 2):
@@ -351,14 +366,15 @@ class SkillLearningService:
         return effects
 
     @staticmethod
-    def _is_confirmed_positive_run(record: RunRecord) -> bool:
-        validation = record.validation_result or {}
+    def _is_task_accepted_run(record: RunRecord) -> bool:
         feedback = record.feedback or {}
+        acceptance_type = feedback.get("acceptance_type")
+        if acceptance_type is None and feedback.get("feedback_type") == "satisfied":
+            acceptance_type = "accept"
         return (
             bool(record.success)
             and bool(record.task_id)
-            and validation.get("accepted") is True
-            and feedback.get("feedback_type") == "satisfied"
+            and acceptance_type == "accept"
         )
 
     @staticmethod

app-instance/backend/beaver/tasks/__init__.py

@@ -6,7 +6,6 @@ from .planner import TaskExecutionPlan, TaskExecutionPlanner
 from .router import MainAgentRouter
 from .service import TaskService
 from .skill_resolver import SkillResolutionReport, TaskSkillResolver
-from .validation import ValidationService
 
 __all__ = [
     "EvidenceBuilder",
@@ -24,6 +23,5 @@ __all__ = [
     "ToolEvidence",
     "ValidationResult",
     "ValidationStatus",
-    "ValidationService",
     "render_task_evidence",
 ]

app-instance/backend/beaver/tasks/models.py

@@ -1,4 +1,4 @@
-"""Models for internal task tracking and validation."""
+"""Models for internal task tracking and user acceptance."""
 
 from __future__ import annotations
 
@@ -9,7 +9,12 @@ from typing import Any, Literal
 ValidationStatus = Literal["accepted", "rejected", "insufficient_evidence", "validator_error"]
 
 VALIDATION_STATUSES = {"accepted", "rejected", "insufficient_evidence", "validator_error"}
-TASK_OPEN_STATUSES = {"open", "running", "validating", "awaiting_feedback", "needs_review", "needs_revision"}
+TASK_OPEN_STATUSES = {"open", "running", "awaiting_acceptance", "needs_revision"}
+LEGACY_STATUS_MAP = {
+    "validating": "running",
+    "awaiting_feedback": "awaiting_acceptance",
+    "needs_review": "awaiting_acceptance",
+}
 
 
 @dataclass(slots=True)
@@ -113,11 +118,11 @@ class TaskRecord:
 
     @property
     def is_execution_active(self) -> bool:
-        return self.status in {"running", "validating"}
+        return self.status == "running"
 
     @property
     def requires_user_action(self) -> bool:
-        return self.status in {"awaiting_feedback", "needs_review", "needs_revision"}
+        return self.status in {"awaiting_acceptance", "needs_revision"}
 
     def to_dict(self) -> dict[str, Any]:
         return {
@@ -137,6 +142,7 @@ class TaskRecord:
             "satisfaction": self.satisfaction,
             "run_ids": list(self.run_ids),
             "skill_names": list(self.skill_names),
+            "acceptance": list(self.feedback),
             "feedback": list(self.feedback),
             "validation_result": self.validation_result,
             "metadata": dict(self.metadata),
@@ -152,7 +158,7 @@ class TaskRecord:
             goal=str(payload.get("goal") or payload.get("description") or ""),
             constraints=[str(item) for item in payload.get("constraints") or []],
             priority=int(payload.get("priority", 0) or 0),
-            status=str(payload.get("status") or "open"),
+            status=LEGACY_STATUS_MAP.get(str(payload.get("status") or "open"), str(payload.get("status") or "open")),
             creator=str(payload.get("creator") or "main-agent"),
             created_at=str(payload.get("created_at") or ""),
             updated_at=str(payload.get("updated_at") or ""),
@@ -161,7 +167,11 @@ class TaskRecord:
             satisfaction=_optional_float(payload.get("satisfaction")),
             run_ids=[str(item) for item in payload.get("run_ids") or []],
             skill_names=[str(item) for item in payload.get("skill_names") or []],
-            feedback=[dict(item) for item in payload.get("feedback") or [] if isinstance(item, dict)],
+            feedback=[
+                _normalize_acceptance_entry(dict(item))
+                for item in (payload.get("acceptance") or payload.get("feedback") or [])
+                if isinstance(item, dict)
+            ],
             validation_result=dict(payload["validation_result"]) if isinstance(payload.get("validation_result"), dict) else None,
             metadata=dict(payload.get("metadata") or {}),
         )
@@ -226,3 +236,13 @@ def _optional_float(value: Any) -> float | None:
     if value in (None, ""):
         return None
     return float(value)
+
+
+def _normalize_acceptance_entry(entry: dict[str, Any]) -> dict[str, Any]:
+    if entry.get("acceptance_type") is None and entry.get("feedback_type") is not None:
+        feedback_type = str(entry.get("feedback_type") or "")
+        entry["acceptance_type"] = "accept" if feedback_type == "satisfied" else feedback_type
+    if entry.get("feedback_type") is None and entry.get("acceptance_type") is not None:
+        acceptance_type = str(entry.get("acceptance_type") or "")
+        entry["feedback_type"] = "satisfied" if acceptance_type == "accept" else acceptance_type
+    return entry

app-instance/backend/beaver/tasks/planner.py

@@ -10,7 +10,7 @@ from typing import Any, Literal
 from beaver.coordinator.models import AgentDescriptor, ExecutionGraph, ExecutionNode
 from beaver.engine.providers import ProviderBundle
 
-from .models import TaskRecord, ValidationResult
+from .models import TaskRecord
 from .skill_resolver import SkillResolutionReport, TaskSkillResolver
 
 
@@ -76,7 +76,6 @@ class TaskExecutionPlanner:
         task: TaskRecord,
         user_message: str,
         attempt_index: int,
-        latest_validation: ValidationResult | None = None,
         provider_bundle: ProviderBundle | None = None,
         timeout_seconds: float = 30.0,
     ) -> TaskExecutionPlan:
@@ -105,7 +104,6 @@ class TaskExecutionPlanner:
                                 task=task,
                                 user_message=user_message,
                                 attempt_index=attempt_index,
-                                latest_validation=latest_validation,
                             ),
                         },
                     ],
@@ -230,14 +228,10 @@ class TaskExecutionPlanner:
         task: TaskRecord,
         user_message: str,
         attempt_index: int,
-        latest_validation: ValidationResult | None,
     ) -> str:
-        validation_note = ""
-        if latest_validation is not None:
-            validation_note = (
-                "\nPrevious validation issues:\n"
-                + json.dumps(latest_validation.to_dict(), ensure_ascii=False)
-            )
+        history_note = ""
+        if task.feedback:
+            history_note = "\nRelevant task history:\n" + json.dumps(task.feedback[-5:], ensure_ascii=False)
         return (
             "Decide execution mode for this internal Task attempt.\n"
             "Use mode=team only when independent research, review, implementation slices, or staged checks "
@@ -254,7 +248,7 @@ class TaskExecutionPlanner:
             f"Task goal:\n{task.goal}\n\n"
             f"Current user request:\n{user_message}\n\n"
             f"Attempt index: {attempt_index}\n"
-            f"{validation_note}"
+            f"{history_note}"
         )
 
     @staticmethod

app-instance/backend/beaver/tasks/service.py

@@ -7,7 +7,7 @@ from pathlib import Path
 from typing import Any
 from uuid import uuid4
 
-from .models import TaskEvent, TaskRecord, ValidationResult
+from .models import TaskEvent, TaskRecord
 from .store import TaskStore
 
 
@@ -105,38 +105,70 @@ class TaskService:
         for name in skill_names or []:
             if name not in task.skill_names:
                 task.skill_names.append(name)
+        task.status = "awaiting_acceptance"
         task.updated_at = self._now()
         self.store.upsert_task(task)
         self._event(task, "run_completed", run_id=run_id, payload={"skill_names": skill_names or []})
+        self._event(task, "evidence_recorded", run_id=run_id, payload={"skill_names": skill_names or []})
         return task
 
-    def record_validation(
+    def add_acceptance(
         self,
         task_id: str,
-        run_id: str,
-        validation: ValidationResult,
         *,
-        final_attempt: bool = True,
-        has_usable_answer: bool = True,
+        acceptance_type: str,
+        comment: str | None = None,
+        run_id: str | None = None,
     ) -> TaskRecord:
         task = self._require(task_id)
         now = self._now()
-        if validation.status == "accepted":
-            task.status = "awaiting_feedback"
-        elif validation.status in {"insufficient_evidence", "validator_error"}:
-            task.status = "needs_review"
-        elif validation.status == "rejected" and not final_attempt:
+        normalized = normalize_acceptance_type(acceptance_type)
+        matching_acceptance = any(
+            item.get("run_id") == run_id and item.get("acceptance_type") == normalized
+            for item in task.feedback
+        )
+        conflicting_acceptance = next(
+            (
+                item
+                for item in task.feedback
+                if item.get("run_id") == run_id and item.get("acceptance_type") != normalized
+            ),
+            None,
+        )
+        if conflicting_acceptance is not None:
+            raise ValueError(
+                f"Acceptance for run_id={run_id!r} was already recorded as "
+                f"{conflicting_acceptance.get('acceptance_type')!r}"
+            )
+        if task.status in {"closed", "abandoned"} and not matching_acceptance:
+            raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
+        if matching_acceptance:
+            return task
+
+        entry = {
+            "acceptance_type": normalized,
+            "feedback_type": "satisfied" if normalized == "accept" else normalized,
+            "comment": comment or "",
+            "run_id": run_id,
+            "created_at": now,
+        }
+        task.feedback.append(entry)
+        if normalized == "revise":
             task.status = "needs_revision"
-        elif validation.status == "rejected" and has_usable_answer:
-            task.status = "needs_review"
-        else:
-            task.status = "failed"
+        elif normalized == "abandon":
+            task.status = "abandoned"
             task.closed_at = now
-            task.close_reason = "automatic validation rejected the final attempt"
+            task.close_reason = comment or "abandoned"
+        elif normalized == "accept":
+            task.status = "closed"
+            task.closed_at = now
+            task.close_reason = "accepted"
+            task.satisfaction = 1.0
+            if run_id:
+                task.metadata["final_accepted_run_id"] = run_id
         task.updated_at = now
-        task.validation_result = validation.to_dict()
         self.store.upsert_task(task)
-        self._event(task, "validated", run_id=run_id, payload=validation.to_dict())
+        self._event(task, f"acceptance_{normalized}", run_id=run_id, payload=entry)
         return task
 
     def add_feedback(
@@ -147,52 +179,12 @@ class TaskService:
         comment: str | None = None,
         run_id: str | None = None,
     ) -> TaskRecord:
-        task = self._require(task_id)
-        now = self._now()
-        matching_feedback = any(
-            item.get("run_id") == run_id and item.get("feedback_type") == feedback_type
-            for item in task.feedback
+        return self.add_acceptance(
+            task_id,
+            acceptance_type=feedback_type,
+            comment=comment,
+            run_id=run_id,
         )
-        conflicting_feedback = next(
-            (
-                item
-                for item in task.feedback
-                if item.get("run_id") == run_id and item.get("feedback_type") != feedback_type
-            ),
-            None,
-        )
-        if conflicting_feedback is not None:
-            raise ValueError(
-                f"Feedback for run_id={run_id!r} was already recorded as "
-                f"{conflicting_feedback.get('feedback_type')!r}"
-            )
-        if task.status in {"closed", "abandoned"} and not matching_feedback:
-            raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
-        if matching_feedback:
-            return task
-
-        entry = {
-            "feedback_type": feedback_type,
-            "comment": comment or "",
-            "run_id": run_id,
-            "created_at": now,
-        }
-        task.feedback.append(entry)
-        if feedback_type == "revise":
-            task.status = "needs_revision"
-        elif feedback_type == "abandon":
-            task.status = "abandoned"
-            task.closed_at = now
-            task.close_reason = comment or "abandoned"
-        elif feedback_type == "satisfied":
-            task.status = "closed"
-            task.closed_at = now
-            task.close_reason = "satisfied"
-            task.satisfaction = 1.0
-        task.updated_at = now
-        self.store.upsert_task(task)
-        self._event(task, f"feedback_{feedback_type}", run_id=run_id, payload=entry)
-        return task
 
     def close_task(self, task_id: str, *, reason: str = "closed") -> TaskRecord:
         task = self._require(task_id)
@@ -267,3 +259,12 @@ def short_task_title(text: str) -> str:
     if len(words) <= 4:
         return cleaned[:40]
     return " ".join(words[:4])[:40]
+
+
+def normalize_acceptance_type(value: str) -> str:
+    normalized = (value or "").strip().lower()
+    if normalized == "satisfied":
+        return "accept"
+    if normalized not in {"accept", "revise", "abandon"}:
+        raise ValueError("acceptance_type must be one of: accept, revise, abandon")
+    return normalized

app-instance/backend/beaver/tasks/validation.py

@@ -1,154 +0,0 @@
-"""Automatic validation for internal Task mode."""
-
-from __future__ import annotations
-
-import json
-from typing import Any
-
-from beaver.engine.providers import ProviderBundle
-
-from .models import TaskRecord, ValidationResult
-
-
-class ValidationService:
-    async def validate_task_result(
-        self,
-        *,
-        task: TaskRecord,
-        user_message: str,
-        final_output: str,
-        evidence_packet: Any | None = None,
-        evidence_text: str = "",
-        transcript_excerpt: str = "",
-        tool_summaries: list[str] | None = None,
-        team_summaries: list[str] | None = None,
-        provider_bundle: ProviderBundle | None = None,
-    ) -> ValidationResult:
-        provider = None
-        model = None
-        if provider_bundle is not None:
-            provider = provider_bundle.auxiliary_provider or provider_bundle.main_provider
-            runtime = provider_bundle.auxiliary_runtime or provider_bundle.main_runtime
-            model = getattr(runtime, "model", None)
-        if provider is not None:
-            try:
-                return await self._validate_with_provider(
-                    provider=provider,
-                    model=model,
-                    task=task,
-                    user_message=user_message,
-                    final_output=final_output,
-                    evidence_text=evidence_text,
-                    transcript_excerpt=transcript_excerpt,
-                    tool_summaries=tool_summaries or [],
-                    team_summaries=team_summaries or [],
-                )
-            except Exception as exc:
-                return ValidationResult(
-                    status="validator_error",
-                    score=0.0,
-                    issues=[f"Validator failed: {exc}"],
-                    evidence_gaps=["Automatic validation failed before producing a reliable decision."],
-                    missing_requirements=["User review is required because automatic validation failed."],
-                    recommended_revision_prompt=(
-                        "Review the answer and evidence, then decide whether to revise or accept it."
-                    ),
-                    validator="llm_error",
-                )
-        return self._heuristic_validate(final_output)
-
-    async def _validate_with_provider(
-        self,
-        *,
-        provider: Any,
-        model: str | None,
-        task: TaskRecord,
-        user_message: str,
-        final_output: str,
-        evidence_text: str,
-        transcript_excerpt: str,
-        tool_summaries: list[str],
-        team_summaries: list[str],
-    ) -> ValidationResult:
-        legacy_context = "" if evidence_text else (
-            f"Transcript excerpt:\n{transcript_excerpt}\n\n"
-            f"Tool summaries:\n{json.dumps(tool_summaries, ensure_ascii=False)}\n\n"
-            f"Team summaries:\n{json.dumps(team_summaries, ensure_ascii=False)}\n\n"
-        )
-        prompt = (
-            "Validate whether the assistant output satisfies the task. "
-            "Return only compact JSON with keys: passed, score, issues, "
-            "missing_requirements, recommended_revision_prompt.\n\n"
-            f"Task goal:\n{task.goal}\n\n"
-            f"Current user request:\n{user_message}\n\n"
-            f"Evidence packet:\n{evidence_text}\n\n"
-            f"{legacy_context}"
-            f"Assistant final output:\n{final_output}"
-        )
-        response = await provider.chat(
-            messages=[
-                {"role": "system", "content": "You are a strict task result validator."},
-                {"role": "user", "content": prompt},
-            ],
-            tools=None,
-            model=model,
-            max_tokens=4096,
-            temperature=0.0,
-        )
-        payload = self._parse_json_object(response.content or "")
-        status = payload.get("status")
-        if status not in {"accepted", "rejected", "insufficient_evidence", "validator_error"}:
-            status = (
-                "accepted"
-                if payload.get("passed") and float(payload.get("score", 0.0) or 0.0) >= 0.75
-                else "rejected"
-            )
-        return ValidationResult(
-            status=status,
-            score=max(0.0, min(1.0, float(payload.get("score", 0.0) or 0.0))),
-            issues=[str(item) for item in payload.get("issues") or []],
-            missing_requirements=[str(item) for item in payload.get("missing_requirements") or []],
-            evidence_gaps=[str(item) for item in payload.get("evidence_gaps") or []],
-            recommended_revision_prompt=str(payload.get("recommended_revision_prompt") or ""),
-            validator="llm",
-        )
-
-    @staticmethod
-    def _heuristic_validate(final_output: str) -> ValidationResult:
-        text = final_output.strip()
-        if not text:
-            return ValidationResult(
-                passed=False,
-                score=0.0,
-                issues=["Assistant output is empty."],
-                missing_requirements=["A non-empty result is required."],
-                recommended_revision_prompt="Produce a complete, non-empty answer for the task.",
-                validator="heuristic",
-            )
-        lowered = text.lower()
-        if "run failed before completion" in lowered or "tool loop stopped" in lowered:
-            return ValidationResult(
-                passed=False,
-                score=0.35,
-                issues=["The run did not complete cleanly."],
-                missing_requirements=["A successful final result is required."],
-                recommended_revision_prompt="Retry the task and address the failure before returning the final answer.",
-                validator="heuristic",
-            )
-        return ValidationResult(passed=True, score=0.85, validator="heuristic")
-
-    @staticmethod
-    def _parse_json_object(text: str) -> dict[str, Any]:
-        cleaned = text.strip()
-        if cleaned.startswith("```"):
-            cleaned = cleaned.strip("`")
-            if cleaned.lower().startswith("json"):
-                cleaned = cleaned[4:].strip()
-        start = cleaned.find("{")
-        end = cleaned.rfind("}")
-        if start >= 0 and end >= start:
-            cleaned = cleaned[start : end + 1]
-        payload = json.loads(cleaned)
-        if not isinstance(payload, dict):
-            raise ValueError("validator response must be a JSON object")
-        return payload