fix(growth,skills,kernel): Phase 0 地基修复 — 经验积累覆盖 + Skill 工具调用

Bug 1: ExperienceStore store_experience() 相同 pain_pattern 因确定性 URI
直接覆盖，新 Experience reuse_count=0 重置已有积累。修复为先检查 URI
是否已存在，若存在则合并（保留原 id/created_at，reuse_count+1）。

Bug 2: PromptOnlySkill::execute() 只做纯文本 complete()，75 个 Skill
的 tools 字段是装饰性的。修复为扩展 LlmCompleter 支持 complete_with_tools，
SkillContext 新增 tool_definitions，KernelSkillExecutor 从 ToolRegistry
解析 manifest 声明的工具定义传入 LLM function calling。

crates/zclaw-kernel/src/kernel/adapters.rs

@@ -6,9 +6,9 @@ use async_trait::async_trait;
 use serde_json::{json, Value};
 
 use zclaw_runtime::{LlmDriver, tool::{SkillExecutor, HandExecutor}};
-use zclaw_skills::{SkillRegistry, LlmCompleter};
+use zclaw_skills::{SkillRegistry, LlmCompleter, SkillCompletion, SkillToolCall};
 use zclaw_hands::HandRegistry;
-use zclaw_types::{AgentId, Result};
+use zclaw_types::{AgentId, Result, ToolDefinition};
 
 /// Adapter that bridges `zclaw_runtime::LlmDriver` -> `zclaw_skills::LlmCompleter`
 pub(crate) struct LlmDriverAdapter {
@@ -44,18 +44,111 @@ impl LlmCompleter for LlmDriverAdapter {
             Ok(text)
         })
     }
+
+    fn complete_with_tools(
+        &self,
+        prompt: &str,
+        system_prompt: Option<&str>,
+        tools: Vec<ToolDefinition>,
+    ) -> Pin<Box<dyn std::future::Future<Output = std::result::Result<SkillCompletion, String>> + Send + '_>> {
+        let driver = self.driver.clone();
+        let prompt = prompt.to_string();
+        let system = system_prompt.map(|s| s.to_string());
+        let max_tokens = self.max_tokens;
+        let temperature = self.temperature;
+        Box::pin(async move {
+            let mut messages = Vec::new();
+            messages.push(zclaw_types::Message::user(prompt));
+
+            let request = zclaw_runtime::CompletionRequest {
+                model: String::new(),
+                system,
+                messages,
+                tools,
+                max_tokens: Some(max_tokens),
+                temperature: Some(temperature),
+                stop: Vec::new(),
+                stream: false,
+                thinking_enabled: false,
+                reasoning_effort: None,
+                plan_mode: false,
+            };
+            let response = driver.complete(request).await
+                .map_err(|e| format!("LLM completion error: {}", e))?;
+
+            let mut text_parts = Vec::new();
+            let mut tool_calls = Vec::new();
+            for block in &response.content {
+                match block {
+                    zclaw_runtime::ContentBlock::Text { text } => {
+                        text_parts.push(text.clone());
+                    }
+                    zclaw_runtime::ContentBlock::ToolUse { id, name, input } => {
+                        tool_calls.push(SkillToolCall {
+                            id: id.clone(),
+                            name: name.clone(),
+                            input: input.clone(),
+                        });
+                    }
+                    _ => {}
+                }
+            }
+
+            Ok(SkillCompletion {
+                text: text_parts.join(""),
+                tool_calls,
+            })
+        })
+    }
 }
 
 /// Skill executor implementation for Kernel
 pub struct KernelSkillExecutor {
     pub(crate) skills: Arc<SkillRegistry>,
     pub(crate) llm: Arc<dyn LlmCompleter>,
+    /// Shared tool registry, updated before each skill execution from the
+    /// agent loop's freshly-built registry. Uses std::sync because reads
+    /// happen from async code but writes are brief and infrequent.
+    pub(crate) tool_registry: std::sync::RwLock<Option<zclaw_runtime::ToolRegistry>>,
 }
 
 impl KernelSkillExecutor {
     pub fn new(skills: Arc<SkillRegistry>, driver: Arc<dyn LlmDriver>) -> Self {
-        let llm: Arc<dyn zclaw_skills::LlmCompleter> = Arc::new(LlmDriverAdapter { driver, max_tokens: 4096, temperature: 0.7 });
-        Self { skills, llm }
+        let llm: Arc<dyn LlmCompleter> = Arc::new(LlmDriverAdapter { driver, max_tokens: 4096, temperature: 0.7 });
+        Self { skills, llm, tool_registry: std::sync::RwLock::new(None) }
+    }
+
+    /// Update the tool registry snapshot. Called by the kernel before each
+    /// agent loop iteration so skill execution sees the latest tool set.
+    pub fn set_tool_registry(&self, registry: zclaw_runtime::ToolRegistry) {
+        if let Ok(mut guard) = self.tool_registry.write() {
+            *guard = Some(registry);
+        }
+    }
+
+    /// Resolve the tool definitions declared by a skill manifest against
+    /// the currently active tool registry.
+    fn resolve_tool_definitions(&self, skill_id: &str) -> Vec<ToolDefinition> {
+        let manifests = self.skills.manifests_snapshot();
+        let manifest = match manifests.get(&zclaw_types::SkillId::new(skill_id)) {
+            Some(m) => m,
+            None => return vec![],
+        };
+        if manifest.tools.is_empty() {
+            return vec![];
+        }
+        let guard = match self.tool_registry.read() {
+            Ok(g) => g,
+            Err(_) => return vec![],
+        };
+        let registry = match guard.as_ref() {
+            Some(r) => r,
+            None => return vec![],
+        };
+        // Only include definitions for tools declared in the skill manifest.
+        registry.definitions().into_iter()
+            .filter(|def| manifest.tools.iter().any(|t| t == &def.name))
+            .collect()
     }
 }
 
@@ -68,10 +161,12 @@ impl SkillExecutor for KernelSkillExecutor {
         session_id: &str,
         input: Value,
     ) -> Result<Value> {
+        let tool_definitions = self.resolve_tool_definitions(skill_id);
         let context = zclaw_skills::SkillContext {
             agent_id: agent_id.to_string(),
             session_id: session_id.to_string(),
             llm: Some(self.llm.clone()),
+            tool_definitions,
             ..Default::default()
         };
         let result = self.skills.execute(&zclaw_types::SkillId::new(skill_id), &context, input).await?;

crates/zclaw-kernel/src/kernel/messaging.rs

@@ -56,6 +56,7 @@ impl Kernel {
         // Create agent loop with model configuration
         let subagent_enabled = chat_mode.as_ref().and_then(|m| m.subagent_enabled).unwrap_or(false);
         let tools = self.create_tool_registry(subagent_enabled);
+        self.skill_executor.set_tool_registry(tools.clone());
         let mut loop_runner = AgentLoop::new(
             *agent_id,
             self.driver.clone(),
@@ -169,6 +170,7 @@ impl Kernel {
         // Create agent loop with model configuration
         let subagent_enabled = chat_mode.as_ref().and_then(|m| m.subagent_enabled).unwrap_or(false);
         let tools = self.create_tool_registry(subagent_enabled);
+        self.skill_executor.set_tool_registry(tools.clone());
         let mut loop_runner = AgentLoop::new(
             *agent_id,
             self.driver.clone(),