fix(agent): include tools schema in context-window budget

mateclaw-server/src/main/java/vip/mate/agent/AgentGraphBuilder.java

@@ -303,7 +303,7 @@ public class AgentGraphBuilder {
         String reasoningEffort = resolveReasoningEffortForModel(runtimeModel);
         CompiledGraph compiledGraph = buildReActGraph(toolSet, chatModel, maxIter, reasoningEffort, runtimeModel, agentId);
         return new StateGraphReActAgent(chatClient, conversationService, compiledGraph,
-                chatModel, conversationWindowManager);
+                chatModel, conversationWindowManager, toolSet);
     }
 
     StateGraphPlanExecuteAgent buildPlanExecuteAgent(AgentToolSet toolSet, ModelConfigEntity runtimeModel, int maxIter) {
@@ -317,7 +317,7 @@ public class AgentGraphBuilder {
         String reasoningEffort = resolveReasoningEffortForModel(runtimeModel);
         CompiledGraph graph = buildPlanExecuteGraph(toolSet, chatModel, maxIter, reasoningEffort, runtimeModel, agentId);
         return new StateGraphPlanExecuteAgent(chatClient, conversationService, graph, planningService,
-                chatModel, conversationWindowManager);
+                chatModel, conversationWindowManager, toolSet);
     }
 
     CompiledGraph buildPlanExecuteGraph(AgentToolSet toolSet, ChatModel chatModel, int maxIterations, String reasoningEffort) {

mateclaw-server/src/main/java/vip/mate/agent/context/ConversationWindowManager.java

@@ -11,6 +11,7 @@ import org.springframework.ai.chat.model.ChatModel;
 import org.springframework.ai.chat.model.ChatResponse;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.tool.ToolCallback;
 import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
 import org.springframework.stereotype.Component;
 import vip.mate.agent.prompt.PromptLoader;
@@ -116,6 +117,23 @@ public class ConversationWindowManager {
                                      String currentUserMessage,
                                      Integer maxInputTokens, ChatModel chatModel,
                                      String conversationId, Long agentId) {
+        return fitToWindow(messages, systemPrompt, currentUserMessage,
+                maxInputTokens, chatModel, conversationId, agentId, null);
+    }
+
+    /**
+     * Same as the 7-arg overload but additionally accounts for the tool
+     * definitions sent on every LLM call. Without {@code toolCallbacks},
+     * the budget calculation underestimates the actual request size by the
+     * full size of the tools schema (often several thousand tokens for
+     * agents bound to multiple MCP servers), making compression fire too
+     * late and producing HTTP 400 once the request hits the model.
+     */
+    public List<Message> fitToWindow(List<Message> messages, String systemPrompt,
+                                     String currentUserMessage,
+                                     Integer maxInputTokens, ChatModel chatModel,
+                                     String conversationId, Long agentId,
+                                     java.util.Collection<ToolCallback> toolCallbacks) {
         if (messages == null || messages.isEmpty()) {
             return messages;
         }
@@ -127,20 +145,21 @@ public class ConversationWindowManager {
         int systemTokens = TokenEstimator.estimateTokens(systemPrompt);
         int currentMsgTokens = TokenEstimator.estimateTokens(currentUserMessage) + TokenEstimator.PER_MESSAGE_OVERHEAD;
         int historyTokens = TokenEstimator.estimateTokens(messages);
-        int totalTokens = systemTokens + currentMsgTokens + historyTokens;
+        int toolsTokens = TokenEstimator.estimateToolsTokens(toolCallbacks);
+        int totalTokens = systemTokens + currentMsgTokens + historyTokens + toolsTokens;
 
         if (totalTokens <= triggerThreshold) {
             return messages;
         }
 
-        log.info("[ConversationWindow] 超阈值: {} tokens (system={}, current={}, history={}) > {} 触发阈值 (max={}), conv={}",
+        log.info("[ConversationWindow] 超阈值: {} tokens (system={}, current={}, history={}, tools={}) > {} 触发阈值 (max={}), conv={}",
-                totalTokens, systemTokens, currentMsgTokens, historyTokens,
+                totalTokens, systemTokens, currentMsgTokens, historyTokens, toolsTokens,
                 triggerThreshold, effectiveMax, conversationId);
 
         evictExpiredEntries();
 
-        // 可用于历史的 token 预算 = max - system - currentMsg - 安全余量
+        // 可用于历史的 token 预算 = max - system - currentMsg - tools - 安全余量
-        int reservedTokens = systemTokens + currentMsgTokens + (int) (effectiveMax * 0.05);
+        int reservedTokens = systemTokens + currentMsgTokens + toolsTokens + (int) (effectiveMax * 0.05);
         // RFC-025 Change 1: reserve 硬封顶到 effectiveMax 的 50%。
         // 小上下文模型（Ollama 16K、本地 8K）下，systemTokens + currentMsgTokens 很容易
         // 接近或超过 effectiveMax，不封顶会让 historyBudget 变负数导致死循环压缩

mateclaw-server/src/main/java/vip/mate/agent/context/TokenEstimator.java

@@ -1,7 +1,10 @@
 package vip.mate.agent.context;
 
 import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.tool.ToolCallback;
+import org.springframework.ai.tool.definition.ToolDefinition;
 
+import java.util.Collection;
 import java.util.List;
 
 /**
@@ -21,6 +24,13 @@ public final class TokenEstimator {
     /** 每条消息的固定开销 token（role 标记、分隔符等） */
     static final int PER_MESSAGE_OVERHEAD = 4;
 
+    /**
+     * Per-tool wrapper overhead: function/type:object boilerplate, name and
+     * description framing, parameters key, and JSON braces around the schema.
+     * Conservative — slightly overestimates so budget guards don't underrun.
+     */
+    static final int PER_TOOL_OVERHEAD = 12;
+
     private TokenEstimator() {
     }
 
@@ -71,6 +81,38 @@ public final class TokenEstimator {
                 .sum();
     }
 
+    /**
+     * Estimate the token cost of the tool definitions sent on every LLM call
+     * (name + description + JSON inputSchema, plus per-tool wrapper overhead).
+     * <p>
+     * A heavily-bound agent (multiple MCP servers, many built-ins) can carry
+     * several thousand tokens of tool schema on every request — leaving them
+     * out of the context-window budget makes compression decisions fire too
+     * late and on small models triggers HTTP 400 once the request actually
+     * goes out.
+     */
+    public static int estimateToolsTokens(Collection<ToolCallback> callbacks) {
+        if (callbacks == null || callbacks.isEmpty()) {
+            return 0;
+        }
+        int total = 0;
+        for (ToolCallback cb : callbacks) {
+            if (cb == null) continue;
+            ToolDefinition def;
+            try {
+                def = cb.getToolDefinition();
+            } catch (Exception e) {
+                continue;
+            }
+            if (def == null) continue;
+            total += estimateTokens(def.name())
+                    + estimateTokens(def.description())
+                    + estimateTokens(def.inputSchema())
+                    + PER_TOOL_OVERHEAD;
+        }
+        return total;
+    }
+
     /**
      * 判断是否为 CJK 字符（中日韩统一表意文字 + 常用标点）
      */

mateclaw-server/src/main/java/vip/mate/agent/graph/StateGraphReActAgent.java

@@ -53,15 +53,32 @@ public class StateGraphReActAgent extends BaseAgent implements StructuredStreamC
     private final CompiledGraph compiledGraph;
     private final org.springframework.ai.chat.model.ChatModel chatModel;
     private final ConversationWindowManager conversationWindowManager;
+    /**
+     * Held only so {@link #buildInitialState} can include the tools schema in
+     * the context-window budget — those bytes ride along on every LLM call
+     * and were previously ignored, making compression decisions fire late.
+     * Nullable for the legacy 5-arg constructor used by older tests.
+     */
+    private final vip.mate.agent.AgentToolSet toolSet;
 
     public StateGraphReActAgent(ChatClient chatClient, ConversationService conversationService,
                                 CompiledGraph compiledGraph,
                                 org.springframework.ai.chat.model.ChatModel chatModel,
                                 ConversationWindowManager conversationWindowManager) {
+        this(chatClient, conversationService, compiledGraph, chatModel,
+                conversationWindowManager, null);
+    }
+
+    public StateGraphReActAgent(ChatClient chatClient, ConversationService conversationService,
+                                CompiledGraph compiledGraph,
+                                org.springframework.ai.chat.model.ChatModel chatModel,
+                                ConversationWindowManager conversationWindowManager,
+                                vip.mate.agent.AgentToolSet toolSet) {
         super(chatClient, conversationService);
         this.compiledGraph = compiledGraph;
         this.chatModel = chatModel;
         this.conversationWindowManager = conversationWindowManager;
+        this.toolSet = toolSet;
     }
 
     @Override
@@ -372,7 +389,8 @@ public class StateGraphReActAgent extends BaseAgent implements StructuredStreamC
                     maxInputTokens,
                     chatModel,
                     conversationId,
-                    parsedAgentId);
+                    parsedAgentId,
+                    toolSet != null ? toolSet.callbacks() : null);
         }
 
         List<Message> messages = new ArrayList<>(historyMessages);

mateclaw-server/src/main/java/vip/mate/agent/graph/plan/StateGraphPlanExecuteAgent.java

@@ -45,16 +45,28 @@ public class StateGraphPlanExecuteAgent extends BaseAgent implements StructuredS
     private final PlanningService planningService;
     private final org.springframework.ai.chat.model.ChatModel chatModel;
     private final ConversationWindowManager conversationWindowManager;
+    /** Held only so context-window budget includes the tools schema. Nullable for legacy constructor. */
+    private final vip.mate.agent.AgentToolSet toolSet;
 
     public StateGraphPlanExecuteAgent(ChatClient chatClient, ConversationService conversationService,
                                       CompiledGraph compiledGraph, PlanningService planningService,
                                       org.springframework.ai.chat.model.ChatModel chatModel,
                                       ConversationWindowManager conversationWindowManager) {
+        this(chatClient, conversationService, compiledGraph, planningService,
+                chatModel, conversationWindowManager, null);
+    }
+
+    public StateGraphPlanExecuteAgent(ChatClient chatClient, ConversationService conversationService,
+                                      CompiledGraph compiledGraph, PlanningService planningService,
+                                      org.springframework.ai.chat.model.ChatModel chatModel,
+                                      ConversationWindowManager conversationWindowManager,
+                                      vip.mate.agent.AgentToolSet toolSet) {
         super(chatClient, conversationService);
         this.compiledGraph = compiledGraph;
         this.planningService = planningService;
         this.chatModel = chatModel;
         this.conversationWindowManager = conversationWindowManager;
+        this.toolSet = toolSet;
     }
 
     @Override
@@ -254,7 +266,8 @@ public class StateGraphPlanExecuteAgent extends BaseAgent implements StructuredS
                     maxInputTokens,
                     chatModel,
                     conversationId,
-                    parsedAgentId);
+                    parsedAgentId,
+                    toolSet != null ? toolSet.callbacks() : null);
         }
 
         List<Message> messages = new ArrayList<>(historyMessages);