iven
9e0aa496cd
fix(runtime): 修复 Skill/MCP 调用链路3个断点
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1. Anthropic Driver ToolResult 格式修复 — ContentBlock 添加 ToolResult 变体,
tool_call_id 不再被丢弃, 按 Anthropic API 规范发送 tool_result 格式
2. 前端 callMcpTool 参数名对齐 — serviceName/toolName/args 改为
service_name/tool_name/arguments, 后端支持 service_name 精确路由
3. MCP 工具桥接到 ToolRegistry — McpToolAdapter 添加 service_name/clone,
新建 McpToolWrapper 实现 Tool trait, Kernel 添加 mcp_adapters 共享状态,
McpManagerState 与 Kernel 共享同一 Arc<RwLock<Vec>>, MCP 服务启停时
自动同步工具列表到 LLM 可见的 ToolRegistry
2026-04-11 16:20:38 +08:00
iven
14c3c963c2
feat: ask_clarification tool + clarification system prompt + progressive skill loading fix
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- New ask_clarification tool (crates/zclaw-runtime/src/tool/builtin/ask_clarification.rs)
with 5 clarification types: missing_info, ambiguous_requirement, approach_choice, risk_confirmation, suggestion
- Registered as built-in tool in builtin.rs
- Added clarification system prompt instructions to messaging.rs system prompt
- Fixed messaging.rs skill injection: when SkillIndexMiddleware is active,
only inject usage instructions (not full skill list), avoiding duplicate injection
- Fixed pre-existing unicode arrow character causing string literal parse error
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-04-06 13:19:10 +08:00
iven
52bdafa633
refactor(crates): kernel/generation module split + DeerFlow optimizations + middleware + dead code cleanup
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- Split zclaw-kernel/kernel.rs (1486 lines) into 9 domain modules
- Split zclaw-kernel/generation.rs (1080 lines) into 3 modules
- Add DeerFlow-inspired middleware: DanglingTool, SubagentLimit, ToolError, ToolOutputGuard
- Add PromptBuilder for structured system prompt assembly
- Add FactStore (zclaw-memory) for persistent fact extraction
- Add task builtin tool for agent task management
- Driver improvements: Anthropic/OpenAI extended thinking, Gemini safety settings
- Replace let _ = with proper log::warn! across SaaS handlers
- Remove unused dependency (url) from zclaw-hands
2026-04-03 00:28:03 +08:00
iven
04c366fe8b
feat(runtime): DeerFlow 模式中间件链 Phase 1-4 全部完成
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借鉴 DeerFlow 架构，实现完整中间件链系统：
Phase 1 - Agent 中间件链基础设施
- MiddlewareChain Clone 支持
- LoopRunner 双路径集成 (middleware/legacy)
- Kernel create_middleware_chain() 工厂方法
Phase 2 - 技能按需注入
- SkillIndexMiddleware (priority 200)
- SkillLoadTool 工具
- SkillDetail/SkillIndexEntry 结构体
- KernelSkillExecutor trait 扩展
Phase 3 - Guardrail 安全护栏
- GuardrailMiddleware (priority 400, fail_open)
- ShellExecRule / FileWriteRule / WebFetchRule
Phase 4 - 记忆闭环统一
- MemoryMiddleware (priority 150, 30s 防抖)
- after_completion 双路径调用
中间件注册顺序：
100 Compaction | 150 Memory | 200 SkillIndex
400 Guardrail | 500 LoopGuard | 700 TokenCalibration
向后兼容：Option<MiddlewareChain> 默认 None 走旧路径
2026-03-29 23:19:41 +08:00
iven
bf6d81f9c6
refactor: 清理未使用代码并添加未来功能标记
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style: 统一代码格式和注释风格
docs: 更新多个功能文档的完整度和状态
feat(runtime): 添加路径验证工具支持
fix(pipeline): 改进条件判断和变量解析逻辑
test(types): 为ID类型添加全面测试用例
chore: 更新依赖项和Cargo.lock文件
perf(mcp): 优化MCP协议传输和错误处理
2026-03-25 21:55:12 +08:00
iven
504d5746aa
feat(skill-execution): implement execute_skill tool with full execution chain
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- Add ExecuteSkillTool for LLM to call skills during conversation
- Implement SkillExecutor trait in Kernel for skill execution
- Update AgentLoop to support tool execution with skill_executor
- Add default skills_dir configuration in KernelConfig
- Connect frontend skillMarketStore to backend skill_list command
- Update technical documentation with Skill system architecture
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-03-24 13:24:23 +08:00
iven
58cd24f85b
feat: add internal ZCLAW kernel crates to git tracking
2026-03-22 09:26:36 +08:00
