diff --git a/.claude/skills/dingo-verify/scripts/fact_check.py b/.claude/skills/dingo-verify/scripts/fact_check.py
index 23748206..71dd158d 100644
--- a/.claude/skills/dingo-verify/scripts/fact_check.py
+++ b/.claude/skills/dingo-verify/scripts/fact_check.py
@@ -169,13 +169,11 @@ def build_config(
                     "key": api_key,
                     "model": model,
                     "api_url": api_url,
-                    "parameters": {
-                        "temperature": 0,
-                        "agent_config": {
-                            "max_concurrent_claims": max_concurrent,
-                            "max_iterations": 50,
-                            "tools": tools_config,
-                        }
+                    "temperature": 0,
+                    "agent_config": {
+                        "max_concurrent_claims": max_concurrent,
+                        "max_iterations": 50,
+                        "tools": tools_config,
                     }
                 }
             }]
diff --git a/clawhub/scripts/fact_check.py b/clawhub/scripts/fact_check.py
index b2865496..a4930f14 100644
--- a/clawhub/scripts/fact_check.py
+++ b/clawhub/scripts/fact_check.py
@@ -164,13 +164,11 @@ def build_config(
                     "key": api_key,
                     "model": model,
                     "api_url": api_url,
-                    "parameters": {
-                        "temperature": 0,
-                        "agent_config": {
-                            "max_concurrent_claims": max_concurrent,
-                            "max_iterations": 50,
-                            "tools": tools_config,
-                        }
+                    "temperature": 0,
+                    "agent_config": {
+                        "max_concurrent_claims": max_concurrent,
+                        "max_iterations": 50,
+                        "tools": tools_config,
                     }
                 }
             }]
diff --git a/dingo/config/input_args.py b/dingo/config/input_args.py
index df1007a4..de589a69 100644
--- a/dingo/config/input_args.py
+++ b/dingo/config/input_args.py
@@ -102,10 +102,11 @@ class EmbeddingConfigArgs(BaseModel):
 
 
 class EvaluatorLLMArgs(BaseModel):
+    model_config = {"extra": "allow"}
+
     model: Optional[str] = None
     key: Optional[str] = None
     api_url: Optional[str] = None
-    parameters: Optional[dict] = None
     embedding_config: Optional[EmbeddingConfigArgs] = None
 
 
diff --git a/dingo/model/llm/agent/agent_article_fact_checker.py b/dingo/model/llm/agent/agent_article_fact_checker.py
index 1a0006cb..b72b9787 100644
--- a/dingo/model/llm/agent/agent_article_fact_checker.py
+++ b/dingo/model/llm/agent/agent_article_fact_checker.py
@@ -343,23 +343,21 @@ class ArticleFactChecker(BaseAgent):
             "config": {
                 "key": "your-openai-api-key",
                 "model": "gpt-4o-mini",
-                "parameters": {
-                    "agent_config": {
-                        "max_iterations": 10,
-                        "overall_timeout": 900,
-                        "max_concurrent_claims": 5,
-                        "tools": {
-                            "claims_extractor": {
-                                "api_key": "your-openai-api-key",
-                                "max_claims": 50,
-                                "claim_types": ["factual", "institutional", "statistical", "attribution"]
-                            },
-                            "tavily_search": {
-                                "api_key": "your-tavily-api-key",
-                                "max_results": 5
-                            },
-                            "arxiv_search": {"max_results": 5}
-                        }
+                "agent_config": {
+                    "max_iterations": 10,
+                    "overall_timeout": 900,
+                    "max_concurrent_claims": 5,
+                    "tools": {
+                        "claims_extractor": {
+                            "api_key": "your-openai-api-key",
+                            "max_claims": 50,
+                            "claim_types": ["factual", "institutional", "statistical", "attribution"]
+                        },
+                        "tavily_search": {
+                            "api_key": "your-tavily-api-key",
+                            "max_results": 5
+                        },
+                        "arxiv_search": {"max_results": 5}
                     }
                 }
             }
@@ -399,8 +397,8 @@ def _get_output_dir(cls) -> Optional[str]:
         Returns:
             Output directory path (created if needed), or None if saving is disabled.
         """
-        params = cls.dynamic_config.parameters or {}
-        agent_cfg = params.get('agent_config') or {}
+        extra_params = cls.dynamic_config.model_extra
+        agent_cfg = extra_params.get('agent_config') or {}
 
         explicit_path = agent_cfg.get('output_path')
         if explicit_path:
@@ -821,9 +819,8 @@ def eval(cls, input_data: Data) -> EvalDetail:
         output_dir = cls._get_output_dir()
 
         if cls.dynamic_config:
-            if cls.dynamic_config.parameters is None:
-                cls.dynamic_config.parameters = {}
-            cls.dynamic_config.parameters.setdefault("temperature", 0)
+            if 'temperature' not in cls.dynamic_config.model_extra:
+                cls.dynamic_config.temperature = 0
 
         if output_dir and input_data.content:
             cls._save_article_content(output_dir, input_data.content)
@@ -946,8 +943,8 @@ async def _async_extract_claims(cls, input_data: Data) -> List[Dict]:
         """
         from dingo.model.llm.agent.tools.claims_extractor import ClaimsExtractor, ClaimsExtractorConfig
 
-        params = cls.dynamic_config.parameters or {}
-        agent_cfg = params.get('agent_config') or {}
+        extra_params = cls.dynamic_config.model_extra
+        agent_cfg = extra_params.get('agent_config') or {}
         extractor_cfg = agent_cfg.get('tools', {}).get('claims_extractor', {})
 
         config_kwargs: Dict[str, Any] = {
@@ -1043,8 +1040,8 @@ async def _async_verify_single_claim(
     @classmethod
     def _get_max_concurrent_claims(cls) -> int:
         """Read max_concurrent_claims from agent_config or use class default."""
-        params = cls.dynamic_config.parameters or {}
-        agent_cfg = params.get('agent_config') or {}
+        extra_params = cls.dynamic_config.model_extra
+        agent_cfg = extra_params.get('agent_config') or {}
         return agent_cfg.get('max_concurrent_claims', cls.max_concurrent_claims)
 
     @classmethod
@@ -1054,8 +1051,8 @@ def _get_overall_timeout(cls) -> float:
         Returns:
             Positive timeout in seconds, clamped to [30, 7200].
         """
-        params = cls.dynamic_config.parameters or {}
-        agent_cfg = params.get('agent_config') or {}
+        extra_params = cls.dynamic_config.model_extra
+        agent_cfg = extra_params.get('agent_config') or {}
         raw = agent_cfg.get('overall_timeout', cls.overall_timeout)
         try:
             timeout = float(raw)
diff --git a/dingo/model/llm/agent/agent_fact_check.py b/dingo/model/llm/agent/agent_fact_check.py
index 190e105d..5246d7a1 100644
--- a/dingo/model/llm/agent/agent_fact_check.py
+++ b/dingo/model/llm/agent/agent_fact_check.py
@@ -70,15 +70,13 @@ class AgentFactCheck(BaseAgent):
             "key": "your-openai-api-key",
             "api_url": "https://api.openai.com/v1",
             "model": "gpt-4.1-mini-2025-04-14",
-            "parameters": {
-                "agent_config": {
-                    "max_iterations": 5,
-                    "tools": {
-                        "tavily_search": {
-                            "api_key": "your-tavily-api-key",
-                            "max_results": 5,
-                            "search_depth": "advanced"
-                        }
+            "agent_config": {
+                "max_iterations": 5,
+                "tools": {
+                    "tavily_search": {
+                        "api_key": "your-tavily-api-key",
+                        "max_results": 5,
+                        "search_depth": "advanced"
                     }
                 }
             }
diff --git a/dingo/model/llm/agent/agent_hallucination.py b/dingo/model/llm/agent/agent_hallucination.py
index 0e39c48c..fc22ba56 100644
--- a/dingo/model/llm/agent/agent_hallucination.py
+++ b/dingo/model/llm/agent/agent_hallucination.py
@@ -82,15 +82,13 @@ class AgentHallucination(BaseAgent):
             "key": "your-openai-api-key",
             "api_url": "https://api.openai.com/v1",
             "model": "gpt-4.1-mini-2025-04-14",
-            "parameters": {
-                "agent_config": {
-                    "max_iterations": 3,
-                    "tools": {
-                        "tavily_search": {
-                            "api_key": "your-tavily-api-key",
-                            "max_results": 5,
-                            "search_depth": "advanced"
-                        }
+            "agent_config": {
+                "max_iterations": 3,
+                "tools": {
+                    "tavily_search": {
+                        "api_key": "your-tavily-api-key",
+                        "max_results": 5,
+                        "search_depth": "advanced"
                     }
                 }
             }
diff --git a/dingo/model/llm/agent/agent_wrapper.py b/dingo/model/llm/agent/agent_wrapper.py
index 4240c1ef..8c20247d 100644
--- a/dingo/model/llm/agent/agent_wrapper.py
+++ b/dingo/model/llm/agent/agent_wrapper.py
@@ -327,22 +327,22 @@ def get_openai_llm_from_dingo_config(dynamic_config):
             )
 
         # Extract parameters
-        params = dynamic_config.parameters or {}
+        extra_params = dynamic_config.model_extra
 
         # Create ChatOpenAI instance
         llm = ChatOpenAI(
             api_key=dynamic_config.key,
             base_url=dynamic_config.api_url,
             model=dynamic_config.model or "gpt-4.1-mini",
-            temperature=params.get("temperature", 0.3),
-            max_tokens=params.get("max_tokens", 4096),
-            top_p=params.get("top_p", 1.0),
-            timeout=params.get("timeout", 30)
+            temperature=extra_params.get("temperature", 0.3),
+            max_tokens=extra_params.get("max_tokens", 4096),
+            top_p=extra_params.get("top_p", 1.0),
+            timeout=extra_params.get("timeout", 30)
         )
 
         log.debug(
             f"Created ChatOpenAI: model={dynamic_config.model}, "
-            f"temp={params.get('temperature', 0.3)}"
+            f"temp={extra_params.get('temperature', 0.3)}"
         )
 
         return llm
diff --git a/dingo/model/llm/agent/base_agent.py b/dingo/model/llm/agent/base_agent.py
index 3832cefe..d3db23d2 100644
--- a/dingo/model/llm/agent/base_agent.py
+++ b/dingo/model/llm/agent/base_agent.py
@@ -146,7 +146,7 @@ def get_tool_config(cls, tool_name: str) -> Dict[str, Any]:
         Extract tool configuration from agent's dynamic_config.
 
         Configuration is expected in:
-        dynamic_config.parameters.agent_config.tools.{tool_name}
+        dynamic_config.agent_config.tools.{tool_name}
 
         Args:
             tool_name: Name of the tool
@@ -154,8 +154,8 @@ def get_tool_config(cls, tool_name: str) -> Dict[str, Any]:
         Returns:
             Dict of configuration values for the tool
         """
-        params = cls.dynamic_config.parameters or {}
-        agent_config = params.get('agent_config', {})
+        extra_params = cls.dynamic_config.model_extra
+        agent_config = extra_params.get('agent_config', {})
         tools_config = agent_config.get('tools', {})
         return tools_config.get(tool_name, {})
 
@@ -184,8 +184,8 @@ def get_max_iterations(cls) -> int:
         Returns:
             Maximum number of iterations allowed
         """
-        params = cls.dynamic_config.parameters or {}
-        agent_config = params.get('agent_config', {})
+        extra_params = cls.dynamic_config.model_extra
+        agent_config = extra_params.get('agent_config', {})
         return agent_config.get('max_iterations', cls.max_iterations)
 
     @classmethod
diff --git a/dingo/model/llm/base_openai.py b/dingo/model/llm/base_openai.py
index b6fbcd52..c3911699 100644
--- a/dingo/model/llm/base_openai.py
+++ b/dingo/model/llm/base_openai.py
@@ -82,22 +82,18 @@ def send_messages(cls, messages: List):
         else:
             model_name = cls.client.models.list().data[0].id
 
-        params = cls.dynamic_config.parameters
-        cls.validate_config(params)
+        extra_params = cls.dynamic_config.model_extra
+        cls.validate_config(extra_params)
 
         completions = cls.client.chat.completions.create(
             model=model_name,
             messages=messages,
-            temperature=params.get("temperature", 0.3) if params else 0.3,
-            top_p=params.get("top_p", 1) if params else 1,
-            max_tokens=params.get("max_tokens", 4000) if params else 4000,
-            presence_penalty=params.get("presence_penalty", 0) if params else 0,
-            frequency_penalty=params.get("frequency_penalty", 0) if params else 0,
+            **extra_params,
         )
 
         if completions.choices[0].finish_reason == "length":
             raise ExceedMaxTokens(
-                f"Exceed max tokens: {params.get('max_tokens', 4000) if params else 4000}"
+                f"Exceed max tokens: {extra_params.get('max_tokens', 4000)}"
             )
 
         return str(completions.choices[0].message.content)
diff --git a/dingo/model/llm/instruction_quality/llm_instruction_clarity.py b/dingo/model/llm/instruction_quality/llm_instruction_clarity.py
index 9c73a35d..526611d8 100644
--- a/dingo/model/llm/instruction_quality/llm_instruction_clarity.py
+++ b/dingo/model/llm/instruction_quality/llm_instruction_clarity.py
@@ -283,8 +283,8 @@ def process_response(cls, response: str) -> EvalDetail:
 
             # 判断是否通过（默认阈值 6.0）
             threshold = 6.0
-            if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-                threshold = cls.dynamic_config.parameters.get('threshold', 6.0)
+            if hasattr(cls, 'dynamic_config'):
+                threshold = cls.dynamic_config.model_extra.get('threshold', 6.0)
 
             if score >= threshold:
                 result.status = False
diff --git a/dingo/model/llm/instruction_quality/llm_task_difficulty.py b/dingo/model/llm/instruction_quality/llm_task_difficulty.py
index e3fe1db0..9c676396 100644
--- a/dingo/model/llm/instruction_quality/llm_task_difficulty.py
+++ b/dingo/model/llm/instruction_quality/llm_task_difficulty.py
@@ -321,14 +321,14 @@ def process_response(cls, response: str) -> EvalDetail:
 
             # 难度评估没有"通过/不通过"的概念，只是描述性的
             # 但为了兼容框架，我们设置一个合理的默认行为
-            # 可以通过 parameters 配置 min_difficulty 和 max_difficulty
+            # 可以通过 config 中的 min_difficulty 和 max_difficulty 配置难度范围
             result.status = False  # 默认不标记为问题
             result.label = [f"TASK_DIFFICULTY.{difficulty_level.upper()}"]
 
             # 如果配置了难度范围要求，进行检查
-            if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-                min_difficulty = cls.dynamic_config.parameters.get('min_difficulty', 0)
-                max_difficulty = cls.dynamic_config.parameters.get('max_difficulty', 10)
+            if hasattr(cls, 'dynamic_config'):
+                min_difficulty = cls.dynamic_config.model_extra.get('min_difficulty', 0)
+                max_difficulty = cls.dynamic_config.model_extra.get('max_difficulty', 10)
 
                 if difficulty_score < min_difficulty:
                     result.status = True
diff --git a/dingo/model/llm/rag/llm_rag_answer_relevancy.py b/dingo/model/llm/rag/llm_rag_answer_relevancy.py
index ec0e0cda..199187cd 100644
--- a/dingo/model/llm/rag/llm_rag_answer_relevancy.py
+++ b/dingo/model/llm/rag/llm_rag_answer_relevancy.py
@@ -242,14 +242,8 @@ def eval(cls, input_data: Data) -> EvalDetail:
 
         try:
             # 增加温度参数以提高问题生成的随机性
-            if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-                if 'temperature' not in cls.dynamic_config.parameters:
-                    cls.dynamic_config.parameters['temperature'] = 0.7
-            else:
-                # 如果没有parameters，创建一个包含temperature的parameters
-                current_params = cls.dynamic_config.parameters or {}
-                current_params['temperature'] = 0.7
-                cls.dynamic_config.parameters = current_params
+            if hasattr(cls, 'dynamic_config') and 'temperature' not in cls.dynamic_config.model_extra:
+                cls.dynamic_config.temperature = 0.7
 
             # 生成多个相关问题
             generated_questions = cls.generate_multiple_questions(input_data, cls.strictness)
@@ -263,10 +257,9 @@ def eval(cls, input_data: Data) -> EvalDetail:
 
             # 根据分数判断是否通过，默认阈值为5
             threshold = 5
-            if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-                threshold = cls.dynamic_config.parameters.get('threshold', 5)
-                # 检查是否有自定义的strictness参数
-                cls.strictness = cls.dynamic_config.parameters.get('strictness', 3)
+            if hasattr(cls, 'dynamic_config'):
+                threshold = cls.dynamic_config.model_extra.get('threshold', 5)
+                cls.strictness = cls.dynamic_config.model_extra.get('strictness', 3)
 
             # 构建详细的reason文本
             all_reasons = []
diff --git a/dingo/model/llm/rag/llm_rag_context_precision.py b/dingo/model/llm/rag/llm_rag_context_precision.py
index 50f9b661..9c305c4b 100644
--- a/dingo/model/llm/rag/llm_rag_context_precision.py
+++ b/dingo/model/llm/rag/llm_rag_context_precision.py
@@ -256,8 +256,8 @@ def process_response(cls, responses: List[str]) -> EvalDetail:
 
         # 根据分数判断是否通过，默认阈值为5
         threshold = 5
-        if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-            threshold = cls.dynamic_config.parameters.get('threshold', 5)
+        if hasattr(cls, 'dynamic_config'):
+            threshold = cls.dynamic_config.model_extra.get('threshold', 5)
 
         if score >= threshold:
             result.status = False
diff --git a/dingo/model/llm/rag/llm_rag_context_recall.py b/dingo/model/llm/rag/llm_rag_context_recall.py
index 4ba059cc..8d6d06cc 100644
--- a/dingo/model/llm/rag/llm_rag_context_recall.py
+++ b/dingo/model/llm/rag/llm_rag_context_recall.py
@@ -215,8 +215,8 @@ def process_response(cls, response: str) -> EvalDetail:
 
         # 根据分数判断是否通过，默认阈值为5
         threshold = 5
-        if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-            threshold = cls.dynamic_config.parameters.get('threshold', 5)
+        if hasattr(cls, 'dynamic_config'):
+            threshold = cls.dynamic_config.model_extra.get('threshold', 5)
 
         if score >= threshold:
             result.status = False
diff --git a/dingo/model/llm/rag/llm_rag_context_relevancy.py b/dingo/model/llm/rag/llm_rag_context_relevancy.py
index ca16e289..94204e8a 100644
--- a/dingo/model/llm/rag/llm_rag_context_relevancy.py
+++ b/dingo/model/llm/rag/llm_rag_context_relevancy.py
@@ -206,8 +206,8 @@ def process_response(cls, response: str) -> EvalDetail:
 
         # 根据分数判断是否通过，默认阈值为5
         threshold = 5
-        if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-            threshold = cls.dynamic_config.parameters.get('threshold', 5)
+        if hasattr(cls, 'dynamic_config'):
+            threshold = cls.dynamic_config.model_extra.get('threshold', 5)
 
         if score >= threshold:
             result.status = False
diff --git a/dingo/model/llm/rag/llm_rag_faithfulness.py b/dingo/model/llm/rag/llm_rag_faithfulness.py
index 2111e77d..fe763ef0 100644
--- a/dingo/model/llm/rag/llm_rag_faithfulness.py
+++ b/dingo/model/llm/rag/llm_rag_faithfulness.py
@@ -290,8 +290,8 @@ def process_response(cls, response: str) -> EvalDetail:
 
         # 根据分数判断是否通过，默认阈值为5
         threshold = 5
-        if hasattr(cls, 'dynamic_config') and cls.dynamic_config.parameters:
-            threshold = cls.dynamic_config.parameters.get('threshold', 5)
+        if hasattr(cls, 'dynamic_config'):
+            threshold = cls.dynamic_config.model_extra.get('threshold', 5)
 
         if score >= threshold:
             result.status = False
diff --git a/dingo/model/llm/vlm_layout_quality.py b/dingo/model/llm/vlm_layout_quality.py
index 40627a88..e3a5456d 100644
--- a/dingo/model/llm/vlm_layout_quality.py
+++ b/dingo/model/llm/vlm_layout_quality.py
@@ -201,8 +201,8 @@ def send_messages(cls, messages: List):
         else:
             model_name = cls.client.models.list().data[0].id
 
-        params = cls.dynamic_config.parameters
-        cls.validate_config(params)
+        extra_params = cls.dynamic_config.model_extra
+        cls.validate_config(extra_params)
 
         completions = cls.client.chat.completions.create(
             model=model_name,
diff --git a/docs/agent_architecture.md b/docs/agent_architecture.md
index c55d34c6..e563357b 100644
--- a/docs/agent_architecture.md
+++ b/docs/agent_architecture.md
@@ -458,7 +458,7 @@ Aggregation:
                                             ├─ name: "AgentFactCheck"
                                             ├─ config.key: API key
                                             ├─ config.model: "gpt-4"
-                                            └─ config.parameters.agent_config:
+                                            └─ config.agent_config:
                                                  ├─ max_iterations: 10
                                                  └─ tools:
                                                       └─ tavily_search:
@@ -539,7 +539,7 @@ Check if tool in available_tools
 ToolRegistry.get(tool_name) → tool_class
     ↓
 configure_tool(tool_name, tool_class)
-    ├─ Extract config from dynamic_config.parameters.agent_config.tools.{tool_name}
+    ├─ Extract config from dynamic_config.agent_config.tools.{tool_name}
     └─ tool_class.update_config(config_dict)
     ↓
 tool_class.execute(**kwargs)
@@ -560,7 +560,7 @@ Return to agent for processing
 3. **Three Patterns**: LangChain-based (declarative), Custom Workflow (imperative), Agent-First + Context (hybrid)
 4. **Tool System**: Centralized registry with configuration injection
 5. **Execution**: Runs in ThreadPoolExecutor alongside other LLMs
-6. **Configuration**: Nested under `parameters.agent_config` in evaluator config
+6. **Configuration**: `agent_config` is a top-level key in evaluator config (flat structure)
 7. **Artifact Saving**: ArticleFactChecker auto-saves intermediate artifacts to a timestamped directory by default; override via `agent_config.output_path`, or disable with `agent_config.save_artifacts=false`
 
 ### Implementation Checklist
diff --git a/docs/agent_development_guide.md b/docs/agent_development_guide.md
index da071b7c..6d6f80df 100644
--- a/docs/agent_development_guide.md
+++ b/docs/agent_development_guide.md
@@ -441,8 +441,8 @@ def _get_output_dir(cls) -> Optional[str]:
     Get output directory for artifact files (three-priority chain).
     Returns output dir path (created if needed), or None if saving disabled.
     """
-    params = cls.dynamic_config.parameters or {}
-    agent_cfg = params.get('agent_config') or {}
+    extra_params = cls.dynamic_config.model_extra
+    agent_cfg = extra_params.get('agent_config') or {}
 
     explicit_path = agent_cfg.get('output_path')
     if explicit_path:
@@ -673,17 +673,15 @@ class MyAgent(BaseAgent):
             "key": "openai-api-key",
             "api_url": "https://api.openai.com/v1",
             "model": "gpt-4",
-            "parameters": {
-                "agent_config": {
-                    "max_iterations": 3,
-                    "tools": {
-                        "my_tool": {
-                            "api_key": "tool-api-key",
-                            "max_results": 5
-                        }
-                    }
-                }
-            }
+             "agent_config": {
+                 "max_iterations": 3,
+                 "tools": {
+                     "my_tool": {
+                         "api_key": "tool-api-key",
+                         "max_results": 5
+                     }
+                 }
+             }
         }
     }
     """
@@ -889,19 +887,17 @@ def eval(cls, input_data: Data) -> EvalDetail:
         "key": "openai-api-key",
         "api_url": "https://api.openai.com/v1",
         "model": "gpt-4-turbo",
-        "parameters": {
-          "temperature": 0.1,
-          "agent_config": {
-            "max_iterations": 3,
-            "tools": {
-              "my_tool": {
-                "api_key": "my-tool-api-key",
-                "max_results": 10,
-                "timeout": 30
-              },
-              "another_tool": {
-                "config_key": "value"
-              }
+        "temperature": 0.1,
+        "agent_config": {
+          "max_iterations": 3,
+          "tools": {
+            "my_tool": {
+              "api_key": "my-tool-api-key",
+              "max_results": 10,
+              "timeout": 30
+            },
+            "another_tool": {
+              "config_key": "value"
             }
           }
         }
@@ -919,10 +915,10 @@ def eval(cls, input_data: Data) -> EvalDetail:
 def some_method(cls):
     # Access LLM configuration
     model = cls.dynamic_config.model  # "gpt-4-turbo"
-    temperature = cls.dynamic_config.parameters.get('temperature', 0)
+    temperature = cls.dynamic_config.model_extra.get('temperature', 0)
 
     # Access agent-specific configuration
-    agent_config = cls.dynamic_config.parameters.get('agent_config', {})
+    agent_config = cls.dynamic_config.model_extra.get('agent_config', {})
     max_iterations = agent_config.get('max_iterations', 5)
 
     # Get tool configuration
@@ -966,10 +962,8 @@ class MyAgent(BaseAgent):
 {
   "name": "MyAgent",
   "config": {
-    "parameters": {
-      "agent_config": {
-        "max_iterations": 10
-      }
+    "agent_config": {
+      "max_iterations": 10
     }
   }
 }
@@ -1259,17 +1253,15 @@ Always include SOURCES with specific URLs when you perform web searches."""
     "key": "your-openai-api-key",
     "api_url": "https://api.openai.com/v1",
     "model": "gpt-4-turbo",
-    "parameters": {
-      "temperature": 0.1,
-      "max_tokens": 16384,
-      "agent_config": {
-        "max_iterations": 5,
-        "tools": {
-          "tavily_search": {
-            "api_key": "your-tavily-api-key",
-            "max_results": 5,
-            "search_depth": "advanced"
-          }
+    "temperature": 0.1,
+    "max_tokens": 16384,
+    "agent_config": {
+      "max_iterations": 5,
+      "tools": {
+        "tavily_search": {
+          "api_key": "your-tavily-api-key",
+          "max_results": 5,
+          "search_depth": "advanced"
         }
       }
     }
@@ -1597,11 +1589,9 @@ config = {
                 "key": "openai-key",
                 "api_url": "https://api.openai.com/v1",
                 "model": "gpt-4",
-                "parameters": {
-                    "agent_config": {
-                        "tools": {
-                            "tavily_search": {"api_key": "tavily-key"}
-                        }
+                "agent_config": {
+                    "tools": {
+                        "tavily_search": {"api_key": "tavily-key"}
                     }
                 }
             }
@@ -1632,7 +1622,7 @@ summary = executor.execute()
 
 **Configuration not working:**
 - Check JSON structure matches expected format
-- Verify `parameters.agent_config.tools.{tool_name}` structure
+- Verify `agent_config.tools.{tool_name}` structure
 - Use Pydantic validation to catch config errors early
 
 **Tests failing:**
diff --git a/docs/article_fact_checking_guide.md b/docs/article_fact_checking_guide.md
index 518b0ff3..43d04947 100644
--- a/docs/article_fact_checking_guide.md
+++ b/docs/article_fact_checking_guide.md
@@ -81,24 +81,22 @@ config = {
             "config": {
                 "key": os.getenv("OPENAI_API_KEY"),
                 "model": "deepseek-chat",  # or "gpt-4o-mini" for OpenAI
-                "parameters": {
-                    "agent_config": {
-                        "max_iterations": 15,
-                        "output_path": "outputs/article_factcheck/",  # Optional: save intermediate artifacts
-                        "tools": {
-                            "claims_extractor": {
-                                "api_key": os.getenv("OPENAI_API_KEY"),
-                                "max_claims": 50,
-                                "claim_types": [
-                                    "factual", "statistical", "attribution", "institutional",
-                                    "temporal", "comparative", "monetary", "technical"
-                                ]
-                            },
-                            "tavily_search": {
-                                "api_key": os.getenv("TAVILY_API_KEY")
-                            },
-                            "arxiv_search": {"max_results": 5}
-                        }
+                "agent_config": {
+                    "max_iterations": 15,
+                    "output_path": "outputs/article_factcheck/",  # Optional: save intermediate artifacts
+                    "tools": {
+                        "claims_extractor": {
+                            "api_key": os.getenv("OPENAI_API_KEY"),
+                            "max_claims": 50,
+                            "claim_types": [
+                                "factual", "statistical", "attribution", "institutional",
+                                "temporal", "comparative", "monetary", "technical"
+                            ]
+                        },
+                        "tavily_search": {
+                            "api_key": os.getenv("TAVILY_API_KEY")
+                        },
+                        "arxiv_search": {"max_results": 5}
                     }
                 }
             }
@@ -143,19 +141,17 @@ cat > article_check_config.json << EOF
       "config": {
         "key": "${OPENAI_API_KEY}",
         "model": "deepseek-chat",
-        "parameters": {
-          "agent_config": {
-            "max_iterations": 15,
-            "tools": {
-              "claims_extractor": {
-                "api_key": "${OPENAI_API_KEY}",
-                "max_claims": 50
-              },
-              "tavily_search": {
-                "api_key": "${TAVILY_API_KEY}"
-              },
-              "arxiv_search": {}
-            }
+        "agent_config": {
+          "max_iterations": 15,
+          "tools": {
+            "claims_extractor": {
+              "api_key": "${OPENAI_API_KEY}",
+              "max_claims": 50
+            },
+            "tavily_search": {
+              "api_key": "${TAVILY_API_KEY}"
+            },
+            "arxiv_search": {}
           }
         }
       }
diff --git a/docs/config.md b/docs/config.md
index 6d1f1d4c..a5020ee4 100644
--- a/docs/config.md
+++ b/docs/config.md
@@ -104,26 +104,22 @@ HuggingFace 特定配置：
 
 #### EvaluatorLLMArgs 配置 (evaluator.llm_config.[llm_name])
 
-LLM 配置：
+LLM 配置（支持额外字段，所有额外字段会直接透传给 LLM API）：
 
 | Parameter | Type | Default | Required | Description |
 |-----------|------|---------|----------|-------------|
 | model | str | null | No | 使用的模型名称 |
 | key | str | null | No | API 密钥 |
 | api_url | str | null | No | API URL |
-| parameters | object | null | No | LLM 调参配置 |
-
-##### LLM Parameters 配置
-
-LLM 调参配置：
-
-| Parameter | Type | Default | Description |
-|-----------|------|---------|-------------|
-| temperature | number | 1 | 采样温度，0-2之间 |
-| top_p | number | 1 | 核心采样概率 |
-| max_tokens | number | 4000 | 最大生成token数 |
-| presence_penalty | number | 0 | 存在惩罚，-2.0到2.0之间 |
-| frequency_penalty | number | 0 | 频率惩罚，-2.0到2.0之间 |
+| embedding_config | object | null | No | Embedding 模型独立配置（RAG 评估器使用） |
+| temperature | number | 1 | No | 采样温度，0-2之间 |
+| top_p | number | 1 | No | 核心采样概率 |
+| max_tokens | number | 4000 | No | 最大生成token数 |
+| presence_penalty | number | 0 | No | 存在惩罚，-2.0到2.0之间 |
+| frequency_penalty | number | 0 | No | 频率惩罚，-2.0到2.0之间 |
+| agent_config | object | null | No | Agent 专属配置（max_iterations、tools 等） |
+| threshold | number | - | No | 评估通过阈值（各评估器自定义） |
+| *其他字段* | any | - | No | 所有额外字段直接透传给 LLM API |
 
 ## 配置文件示例
 
@@ -181,13 +177,11 @@ LLM 调参配置：
         "model": "gpt-3.5-turbo",
         "key": "your-api-key",
         "api_url": "https://api.openai.com/v1/chat/completions",
-        "parameters": {
-          "temperature": 1,
-          "top_p": 1,
-          "max_tokens": 4000,
-          "presence_penalty": 0,
-          "frequency_penalty": 0
-        }
+        "temperature": 1,
+        "top_p": 1,
+        "max_tokens": 4000,
+        "presence_penalty": 0,
+        "frequency_penalty": 0
       }
     }
   }
diff --git a/docs/factcheck_guide.md b/docs/factcheck_guide.md
index 4112707f..7abed067 100644
--- a/docs/factcheck_guide.md
+++ b/docs/factcheck_guide.md
@@ -101,9 +101,7 @@ input_data = {
                 "model": "deepseek-chat",
                 "key": "your-api-key",
                 "api_url": "https://api.deepseek.com/v1",
-                "parameters": {
-                    "temperature": 0.1
-                }
+                "temperature": 0.1
             }
         }
     }
diff --git a/docs/factuality_assessment_guide.md b/docs/factuality_assessment_guide.md
index 13680cc2..6f670fcc 100644
--- a/docs/factuality_assessment_guide.md
+++ b/docs/factuality_assessment_guide.md
@@ -59,7 +59,7 @@ LLMFactCheck.dynamic_config = EvaluatorLLMArgs(
     key=os.getenv("OPENAI_API_KEY"),
     api_url=os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1"),
     model=os.getenv("OPENAI_MODEL", "gpt-4o-mini"),
-    parameters={"threshold": 5.0}
+    threshold=5.0
 )
 
 # Prepare data
@@ -108,7 +108,7 @@ input_data = {
                         "model": "gpt-4o-mini",
                         "key": "YOUR_API_KEY",
                         "api_url": "https://api.openai.com/v1",
-                        "parameters": {"threshold": 5.0}
+                        "threshold": 5.0
                     }
                 }
             ]
@@ -142,7 +142,7 @@ LLMFactCheck.dynamic_config = EvaluatorLLMArgs(
     key="YOUR_API_KEY",
     api_url="https://api.openai.com/v1",
     model="gpt-4o-mini",
-    parameters={"threshold": 5.0}  # Range: 0.0-10.0
+    threshold=5.0  # Range: 0.0-10.0
 )
 ```
 
diff --git a/docs/hallucination_detection_guide.md b/docs/hallucination_detection_guide.md
index d6fceea9..4da27e0d 100644
--- a/docs/hallucination_detection_guide.md
+++ b/docs/hallucination_detection_guide.md
@@ -131,7 +131,7 @@ LLMHallucination.dynamic_config = EvaluatorLLMArgs(
     key=os.getenv("OPENAI_API_KEY"),
     api_url=os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1"),
     model=os.getenv("OPENAI_MODEL", "gpt-4o-mini"),
-    parameters={"threshold": 0.5}
+    threshold=0.5
 )
 
 # Prepare data
@@ -218,7 +218,7 @@ LLMHallucination.dynamic_config = EvaluatorLLMArgs(
     key="YOUR_API_KEY",
     api_url="https://api.openai.com/v1",
     model="gpt-4o-mini",
-    parameters={"threshold": 0.5}  # Range: 0.0-1.0
+    threshold=0.5  # Range: 0.0-1.0
 )
 ```
 
diff --git a/docs/instruction_quality_guide.md b/docs/instruction_quality_guide.md
index eb1b08d1..2caae4dc 100644
--- a/docs/instruction_quality_guide.md
+++ b/docs/instruction_quality_guide.md
@@ -197,7 +197,7 @@ input_data = {
                         "model": "deepseek-chat",
                         "key": "your-api-key",
                         "api_url": "https://api.deepseek.com",
-                        "parameters": {"threshold": 6.0}
+                        "threshold": 6.0
                     }
                 }
             ]
@@ -223,10 +223,8 @@ print(f"清晰指令: {summary.num_good}/{summary.total}")
                 "model": "deepseek-chat",
                 "key": "your-api-key",
                 "api_url": "https://api.deepseek.com",
-                "parameters": {
-                    "min_difficulty": 3.0,  # 可选：过滤太简单的
-                    "max_difficulty": 8.0,  # 可选：过滤太难的
-                }
+                "min_difficulty": 3.0,  # 可选：过滤太简单的
+                "max_difficulty": 8.0,  # 可选：过滤太难的
             }
         }
     ]
@@ -303,13 +301,13 @@ python examples/custom/evaluate_instruction_quality.py distribution
 **问题1: 过多简单指令**
 ```python
 # 设置最低难度阈值
-"parameters": {"min_difficulty": 3.0}
+"min_difficulty": 3.0
 ```
 
 **问题2: 指令模糊不清**
 ```python
 # 提高清晰度要求
-"parameters": {"threshold": 7.0}
+"threshold": 7.0
 ```
 
 **问题3: 难度分布不均**
diff --git a/docs/rag_evaluation_metrics.md b/docs/rag_evaluation_metrics.md
index 1c11c5dc..c2fce750 100644
--- a/docs/rag_evaluation_metrics.md
+++ b/docs/rag_evaluation_metrics.md
@@ -86,10 +86,8 @@ llm_config_embedding = {
         "api_url": "https://api.openai.com/v1",
         "key": "YOUR_API_KEY"
     },
-    "parameters": {
-        "strictness": 3,
-        "threshold": 5
-    }
+    "strictness": 3,
+    "threshold": 5
 }
 
 input_data = {
@@ -170,7 +168,8 @@ summary = executor.execute()
         "api_url": "https://api.deepseek.com",
         "key": "YOUR_API_KEY"
     },
-    "parameters": {"strictness": 3, "threshold": 5}
+    "strictness": 3,
+    "threshold": 5
 }
 ```
 
@@ -186,7 +185,8 @@ summary = executor.execute()
         "api_url": "http://localhost:8000/v1",  # Local vLLM/Xinference
         "key": "dummy-key"
     },
-    "parameters": {"strictness": 3, "threshold": 5}
+    "strictness": 3,
+    "threshold": 5
 }
 ```
 
diff --git a/docs/rag_evaluation_metrics_zh.md b/docs/rag_evaluation_metrics_zh.md
index 099addb4..963b02dd 100644
--- a/docs/rag_evaluation_metrics_zh.md
+++ b/docs/rag_evaluation_metrics_zh.md
@@ -123,10 +123,8 @@ input_data = {
                             "api_url": OPENAI_URL,
                             "key": OPENAI_KEY
                         },
-                        "parameters": {
-                            "strictness": 3,
-                            "threshold": 5
-                        }
+                        "strictness": 3,
+                        "threshold": 5
                     }
                 },
                 {
@@ -466,7 +464,7 @@ LLMRAGFaithfulness.dynamic_config = EvaluatorLLMArgs(
     key="YOUR_API_KEY",
     api_url="https://api.openai.com/v1",
     model="gpt-4o-mini",
-    parameters={"threshold": 7}  # 自定义阈值
+    threshold=7  # 自定义阈值
 )
 
 # Answer Relevancy 特殊配置（需要 embedding）⭐
@@ -480,10 +478,8 @@ LLMRAGAnswerRelevancy.dynamic_config = EvaluatorLLMArgs(
         api_url="https://api.openai.com/v1",
         key="YOUR_API_KEY"
     ),
-    parameters={
-        "strictness": 3,  # 生成问题数量
-        "threshold": 5    # 通过阈值
-    }
+    strictness=3,  # 生成问题数量
+    threshold=5    # 通过阈值
 )
 ```
 
@@ -499,7 +495,7 @@ LLMRAGAnswerRelevancy.dynamic_config = EvaluatorLLMArgs(
                     "model": "gpt-4o-mini",
                     "key": "YOUR_API_KEY",
                     "api_url": "https://api.openai.com/v1",
-                    "parameters": {"threshold": 7}
+                    "threshold": 7
                 }
             },
             {
@@ -513,10 +509,8 @@ LLMRAGAnswerRelevancy.dynamic_config = EvaluatorLLMArgs(
                         "api_url": "https://api.openai.com/v1",
                         "key": "YOUR_API_KEY"
                     },
-                    "parameters": {
-                        "strictness": 3,
-                        "threshold": 5
-                    }
+                    "strictness": 3,
+                    "threshold": 5
                 }
             }
         ]
@@ -528,8 +522,8 @@ LLMRAGAnswerRelevancy.dynamic_config = EvaluatorLLMArgs(
 
 | 参数 | 适用指标 | 默认值 | 说明 |
 |------|---------|--------|------|
-| `threshold` | 所有指标 | 5.0 | 通过阈值（0-10），在 `parameters` 中配置 |
-| `strictness` | Answer Relevancy | 3 | 生成问题数量（1-5），在 `parameters` 中配置 |
+| `threshold` | 所有指标 | 5.0 | 通过阈值（0-10），直接在 `config` 中配置 |
+| `strictness` | Answer Relevancy | 3 | 生成问题数量（1-5），直接在 `config` 中配置 |
 | `embedding_config` | Answer Relevancy | - | **必需配置**，包含 `model`（模型名）、`api_url`（服务地址）、`key`（API密钥） |
 
 ## 📊 指标详细说明
diff --git a/docs/technical/technical_all.md b/docs/technical/technical_all.md
index 45833111..212fd15c 100644
--- a/docs/technical/technical_all.md
+++ b/docs/technical/technical_all.md
@@ -220,9 +220,14 @@ dingo 在使用提示词进行评估任务的时候，必须同时使用场景
 + model
 + key
 + api_url
-+ parameters
++ temperature（直接平铺在配置中）
++ top_p
++ max_tokens
++ presence_penalty
++ frequency_penalty
++ agent_config（Agent 评估器专用，包含 max_iterations、tools 等）
 
-需要注意的是参数 [parameters](config.md#parameters) ，这个参数会对模型的推理产生影响，可以设置的值包括:
+LLM 调参配置直接平铺在 `config` 对象中（不再嵌套在 `parameters` 字段下），会对模型推理产生影响，可以设置的值包括:
 + temperature
 + top_p
 + max_tokens
diff --git a/examples/agent/agent_article_fact_checking_example.py b/examples/agent/agent_article_fact_checking_example.py
index 45b0ad60..3071f45f 100644
--- a/examples/agent/agent_article_fact_checking_example.py
+++ b/examples/agent/agent_article_fact_checking_example.py
@@ -58,32 +58,30 @@ def main() -> int:
                             "key": openai_key,
                             "model": "intern-s1-pro",
                             "api_url": "https://chat.intern-ai.org.cn/api/v1/",
-                            "parameters": {
-                                "timeout": 600,
-                                "temperature": 0,  # deterministic output
-                                "agent_config": {
-                                    "max_concurrent_claims": 10,
-                                    "max_iterations": 50,
-                                    # Artifacts auto-saved to outputs/article_factcheck_<timestamp>/
-                                    # Override with: "output_path": "your/custom/path"
-                                    "tools": {
-                                        "claims_extractor": {
-                                            "api_key": openai_key,
-                                            "model": "intern-s1-pro",
-                                            "base_url": "https://chat.intern-ai.org.cn/api/v1/",
-                                            "max_claims": 50,
-                                            "claim_types": [
-                                                "factual", "statistical", "attribution", "institutional",
-                                                "temporal", "comparative", "monetary", "technical"
-                                            ]
-                                        },
-                                        "tavily_search": {
-                                            "api_key": tavily_key
-                                        } if tavily_key else {},
-                                        "arxiv_search": {
-                                            "max_results": 5,
-                                            "fetch_affiliations": True,
-                                        }
+                            "timeout": 600,
+                            "temperature": 0,  # deterministic output
+                            "agent_config": {
+                                "max_concurrent_claims": 10,
+                                "max_iterations": 50,
+                                # Artifacts auto-saved to outputs/article_factcheck_<timestamp>/
+                                # Override with: "output_path": "your/custom/path"
+                                "tools": {
+                                    "claims_extractor": {
+                                        "api_key": openai_key,
+                                        "model": "intern-s1-pro",
+                                        "base_url": "https://chat.intern-ai.org.cn/api/v1/",
+                                        "max_claims": 50,
+                                        "claim_types": [
+                                            "factual", "statistical", "attribution", "institutional",
+                                            "temporal", "comparative", "monetary", "technical"
+                                        ]
+                                    },
+                                    "tavily_search": {
+                                        "api_key": tavily_key
+                                    } if tavily_key else {},
+                                    "arxiv_search": {
+                                        "max_results": 5,
+                                        "fetch_affiliations": True,
                                     }
                                 }
                             }
diff --git a/examples/agent/agent_executor_example.py b/examples/agent/agent_executor_example.py
index 02a57c94..e0970ebc 100644
--- a/examples/agent/agent_executor_example.py
+++ b/examples/agent/agent_executor_example.py
@@ -67,17 +67,15 @@ def main():
                     "key": os.getenv("OPENAI_API_KEY", "your-openai-api-key"),
                     "api_url": os.getenv("OPENAI_API_URL", "https://api.openai.com/v1"),
                     "model": "gpt-4.1-mini-2025-04-14",
-                    "parameters": {
-                        "temperature": 0.1,
-                        "max_tokens": 16384,
-                        "agent_config": {
-                            "max_iterations": 5,
-                            "tools": {
-                                "tavily_search": {
-                                    "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key"),
-                                    "max_results": 5,
-                                    "search_depth": "advanced"
-                                }
+                    "temperature": 0.1,
+                    "max_tokens": 16384,
+                    "agent_config": {
+                        "max_iterations": 5,
+                        "tools": {
+                            "tavily_search": {
+                                "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key"),
+                                "max_results": 5,
+                                "search_depth": "advanced"
                             }
                         }
                     }
diff --git a/examples/agent/agent_hallucination_example.py b/examples/agent/agent_hallucination_example.py
index 6f463152..5f2723ec 100644
--- a/examples/agent/agent_hallucination_example.py
+++ b/examples/agent/agent_hallucination_example.py
@@ -64,14 +64,12 @@ def example_with_context():
                     "key": os.getenv("OPENAI_API_KEY", "your-openai-api-key"),
                     "api_url": os.getenv("OPENAI_API_URL", "https://api.openai.com/v1"),
                     "model": "gpt-4.1-mini-2025-04-14",
-                    "parameters": {
-                        "temperature": 0.1,
-                        "agent_config": {
-                            "max_iterations": 3,
-                            "tools": {
-                                "tavily_search": {
-                                    "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key")
-                                }
+                    "temperature": 0.1,
+                    "agent_config": {
+                        "max_iterations": 3,
+                        "tools": {
+                            "tavily_search": {
+                                "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key")
                             }
                         }
                     }
@@ -155,17 +153,15 @@ def example_without_context():
                     "key": os.getenv("OPENAI_API_KEY", "your-openai-api-key"),
                     "api_url": os.getenv("OPENAI_API_URL", "https://api.openai.com/v1"),
                     "model": "gpt-4.1-mini-2025-04-14",
-                    "parameters": {
-                        "temperature": 0.1,
-                        "agent_config": {
-                            "max_iterations": 3,
-                            "tools": {
-                                "tavily_search": {
-                                    "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key"),
-                                    "max_results": 5,
-                                    "search_depth": "advanced",
-                                    "include_answer": True
-                                }
+                    "temperature": 0.1,
+                    "agent_config": {
+                        "max_iterations": 3,
+                        "tools": {
+                            "tavily_search": {
+                                "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key"),
+                                "max_results": 5,
+                                "search_depth": "advanced",
+                                "include_answer": True
                             }
                         }
                     }
@@ -215,13 +211,11 @@ def example_sdk_usage():
         key=os.getenv("OPENAI_API_KEY", "your-openai-api-key"),
         api_url=os.getenv("OPENAI_API_URL", "https://api.openai.com/v1"),
         model="gpt-4.1-mini-2025-04-14",
-        parameters={
-            "temperature": 0.1,
-            "agent_config": {
-                "tools": {
-                    "tavily_search": {
-                        "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key")
-                    }
+        temperature=0.1,
+        agent_config={
+            "tools": {
+                "tavily_search": {
+                    "api_key": os.getenv("TAVILY_API_KEY", "your-tavily-api-key")
                 }
             }
         }
diff --git a/examples/factcheck/dataset_factcheck_evaluation.py b/examples/factcheck/dataset_factcheck_evaluation.py
index dd3d72d3..4f48eadf 100644
--- a/examples/factcheck/dataset_factcheck_evaluation.py
+++ b/examples/factcheck/dataset_factcheck_evaluation.py
@@ -77,10 +77,8 @@ def evaluate_single_data_example():
     evaluator.dynamic_config.model = OPENAI_MODEL
     evaluator.dynamic_config.key = OPENAI_KEY
     evaluator.dynamic_config.api_url = OPENAI_URL
-    evaluator.dynamic_config.parameters = {
-        "temperature": 0.1,  # 降低随机性以提高一致性
-        "max_tokens": 2000
-    }
+    evaluator.dynamic_config.temperature = 0.1  # 降低随机性以提高一致性
+    evaluator.dynamic_config.max_tokens = 2000
 
     # 创建测试数据
     test_data = Data(
diff --git a/examples/rag/dataset_rag_eval_baseline.py b/examples/rag/dataset_rag_eval_baseline.py
index 84e09106..9828f7e7 100644
--- a/examples/rag/dataset_rag_eval_baseline.py
+++ b/examples/rag/dataset_rag_eval_baseline.py
@@ -128,10 +128,8 @@ def run_rag_evaluation():
             "api_url": OPENAI_URL,  # 如果同一服务提供 embedding
             "key": OPENAI_KEY
         },
-        "parameters": {
-            "strictness": 3,
-            "threshold": 5
-        }
+        "strictness": 3,
+        "threshold": 5
     }
 
     # 构建配置
diff --git a/examples/rag/e2e_RAG_eval_with_mockRAG_fiqa.py b/examples/rag/e2e_RAG_eval_with_mockRAG_fiqa.py
index f212b94b..d190c969 100644
--- a/examples/rag/e2e_RAG_eval_with_mockRAG_fiqa.py
+++ b/examples/rag/e2e_RAG_eval_with_mockRAG_fiqa.py
@@ -327,10 +327,8 @@ def run_dingo_evaluation(rag_output_path: str) -> SummaryModel:
             "api_url": OPENAI_BASE_URL,  # 如果同一服务提供 embedding
             "key": OPENAI_API_KEY
         },
-        "parameters": {
-            "strictness": 3,
-            "threshold": 5
-        }
+        "strictness": 3,
+        "threshold": 5
     }
 
     input_data = {
diff --git a/examples/sft/evaluate_instruction_quality.py b/examples/sft/evaluate_instruction_quality.py
index f9ea43e9..841b54e3 100644
--- a/examples/sft/evaluate_instruction_quality.py
+++ b/examples/sft/evaluate_instruction_quality.py
@@ -56,9 +56,7 @@ def evaluate_instruction_clarity():
                             "model": OPENAI_MODEL,
                             "key": OPENAI_API_KEY,
                             "api_url": OPENAI_BASE_URL,
-                            "parameters": {
-                                "threshold": 6.0  # 清晰度阈值 (0-10)
-                            }
+                            "threshold": 6.0  # 清晰度阈值 (0-10)
                         }
                     }
                 ]
@@ -127,11 +125,9 @@ def evaluate_task_difficulty():
                             "model": OPENAI_MODEL,
                             "key": OPENAI_API_KEY,
                             "api_url": OPENAI_BASE_URL,
-                            "parameters": {
-                                # 可选：设置期望的难度范围
-                                # "min_difficulty": 4.0,  # 最低难度（太简单的会被标记）
-                                # "max_difficulty": 8.0,  # 最高难度（太难的会被标记）
-                            }
+                            # 可选：设置期望的难度范围
+                            # "min_difficulty": 4.0,  # 最低难度（太简单的会被标记）
+                            # "max_difficulty": 8.0,  # 最高难度（太难的会被标记）
                         }
                     }
                 ]
@@ -198,7 +194,7 @@ def evaluate_both():
                             "model": OPENAI_MODEL,
                             "key": OPENAI_API_KEY,
                             "api_url": OPENAI_BASE_URL,
-                            "parameters": {"threshold": 6.0}
+                            "threshold": 6.0
                         }
                     },
                     {
@@ -207,10 +203,8 @@ def evaluate_both():
                             "model": OPENAI_MODEL,
                             "key": OPENAI_API_KEY,
                             "api_url": OPENAI_BASE_URL,
-                            "parameters": {
-                                "min_difficulty": 3.0,  # 过滤太简单的任务
-                                "max_difficulty": 9.0,  # 过滤过于困难的任务
-                            }
+                            "min_difficulty": 3.0,  # 过滤太简单的任务
+                            "max_difficulty": 9.0,  # 过滤过于困难的任务
                         }
                     }
                 ]
diff --git a/mcp_server.py b/mcp_server.py
index b865606c..08f4812d 100644
--- a/mcp_server.py
+++ b/mcp_server.py
@@ -106,11 +106,9 @@ def get_llm_config_from_env(eval_group_name: str = "") -> Dict:
                 "key": openai_key,
                 "api_url": openai_base_url,
                 "model": openai_model,
-                "parameters": {
-                    "temperature": 0.3,
-                    "top_p": 1,
-                    "max_tokens": 4000,
-                }
+                "temperature": 0.3,
+                "top_p": 1,
+                "max_tokens": 4000,
             }
         }
 
diff --git a/skills/dingo-verify/scripts/fact_check.py b/skills/dingo-verify/scripts/fact_check.py
index b2865496..a4930f14 100644
--- a/skills/dingo-verify/scripts/fact_check.py
+++ b/skills/dingo-verify/scripts/fact_check.py
@@ -164,13 +164,11 @@ def build_config(
                     "key": api_key,
                     "model": model,
                     "api_url": api_url,
-                    "parameters": {
-                        "temperature": 0,
-                        "agent_config": {
-                            "max_concurrent_claims": max_concurrent,
-                            "max_iterations": 50,
-                            "tools": tools_config,
-                        }
+                    "temperature": 0,
+                    "agent_config": {
+                        "max_concurrent_claims": max_concurrent,
+                        "max_iterations": 50,
+                        "tools": tools_config,
                     }
                 }
             }]
diff --git a/test/scripts/model/llm/agent/test_article_fact_checker.py b/test/scripts/model/llm/agent/test_article_fact_checker.py
index 5376dfcc..01e12edb 100644
--- a/test/scripts/model/llm/agent/test_article_fact_checker.py
+++ b/test/scripts/model/llm/agent/test_article_fact_checker.py
@@ -552,7 +552,7 @@ def test_get_output_dir_auto_generates_path_when_not_configured(self, tmp_path):
         from dingo.config.input_args import EvaluatorLLMArgs
         ArticleFactChecker.dynamic_config = EvaluatorLLMArgs(
             key="test", api_url="https://api.example.com", model="test",
-            parameters={"agent_config": {"base_output_path": str(tmp_path)}}
+            agent_config={"base_output_path": str(tmp_path)}
         )
         result = ArticleFactChecker._get_output_dir()
         assert result is not None
@@ -565,7 +565,7 @@ def test_get_output_dir_returns_none_when_save_artifacts_disabled(self):
         from dingo.config.input_args import EvaluatorLLMArgs
         ArticleFactChecker.dynamic_config = EvaluatorLLMArgs(
             key="test", api_url="https://api.example.com", model="test",
-            parameters={"agent_config": {"save_artifacts": False}}
+            agent_config={"save_artifacts": False}
         )
         result = ArticleFactChecker._get_output_dir()
         assert result is None
@@ -577,7 +577,7 @@ def test_get_output_dir_creates_directory(self, tmp_path):
         output_dir = str(tmp_path / "new_output_dir")
         ArticleFactChecker.dynamic_config = EvaluatorLLMArgs(
             key="test", api_url="https://api.example.com", model="test",
-            parameters={"agent_config": {"output_path": output_dir}}
+            agent_config={"output_path": output_dir}
         )
 
         result = ArticleFactChecker._get_output_dir()
diff --git a/test/scripts/model/llm/agent/test_async_article_fact_checker.py b/test/scripts/model/llm/agent/test_async_article_fact_checker.py
index f9529f56..43b0bfa8 100644
--- a/test/scripts/model/llm/agent/test_async_article_fact_checker.py
+++ b/test/scripts/model/llm/agent/test_async_article_fact_checker.py
@@ -547,13 +547,13 @@ def setup_method(self):
     def test_returns_class_default_when_no_config(self):
         """Should return max_concurrent_claims class default when not configured."""
         with patch.object(self.checker, 'dynamic_config') as mock_cfg:
-            mock_cfg.parameters = {}
+            mock_cfg.model_extra = {}
             result = self.checker._get_max_concurrent_claims()
         assert result == self.checker.max_concurrent_claims
 
     def test_returns_config_value_when_set(self):
         """Should return value from agent_config.max_concurrent_claims."""
         with patch.object(self.checker, 'dynamic_config') as mock_cfg:
-            mock_cfg.parameters = {"agent_config": {"max_concurrent_claims": 10}}
+            mock_cfg.model_extra = {"agent_config": {"max_concurrent_claims": 10}}
             result = self.checker._get_max_concurrent_claims()
         assert result == 10
diff --git a/test/scripts/skills/test_fact_check_script.py b/test/scripts/skills/test_fact_check_script.py
index 79358e50..aacce4cd 100644
--- a/test/scripts/skills/test_fact_check_script.py
+++ b/test/scripts/skills/test_fact_check_script.py
@@ -189,7 +189,7 @@ def test_tavily_omitted_when_no_key(self):
             max_claims=50,
             max_concurrent=5,
         )
-        tools = config["evaluator"][0]["evals"][0]["config"]["parameters"]["agent_config"]["tools"]
+        tools = config["evaluator"][0]["evals"][0]["config"]["agent_config"]["tools"]
         assert "tavily_search" not in tools
         assert "claims_extractor" in tools
         assert "arxiv_search" in tools
@@ -205,7 +205,7 @@ def test_tavily_included_when_key_present(self):
             max_claims=50,
             max_concurrent=5,
         )
-        tools = config["evaluator"][0]["evals"][0]["config"]["parameters"]["agent_config"]["tools"]
+        tools = config["evaluator"][0]["evals"][0]["config"]["agent_config"]["tools"]
         assert "tavily_search" in tools
         assert tools["tavily_search"]["api_key"] == "tvly-xxx"
 
@@ -220,8 +220,8 @@ def test_temperature_is_zero(self):
             max_claims=50,
             max_concurrent=5,
         )
-        params = config["evaluator"][0]["evals"][0]["config"]["parameters"]
-        assert params["temperature"] == 0
+        cfg = config["evaluator"][0]["evals"][0]["config"]
+        assert cfg["temperature"] == 0
 
 
 class TestErrorOutput: