feat: Step 1 — TaskTypeRegistry + PromptComposer 基础设施

- task_type_registry.py: TaskTypeHandler Protocol (10方法+2属性) + TaskTypeRegistry 注册表
- prompt_composer.py: PromptSection Protocol + PromptContext dataclass + PromptComposer 拼装器
- 零依赖，纯新增文件，不影响现有功能

src/daemon/prompt_composer.py

@@ -0,0 +1,127 @@
+"""
+prompt_composer.py — PromptSection Protocol + PromptContext + PromptComposer
+
+拼装器：有序管理 prompt 段落，按优先级排序后合并为最终 prompt。
+"""
+
+import logging
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
+
+logger = logging.getLogger("moziplus-v2.prompt_composer")
+
+# ---------------------------------------------------------------------------
+# Section 优先级范围约定
+# ---------------------------------------------------------------------------
+PRIORITY_CONTEXT = 10        # 任务上下文
+PRIORITY_PRIOR = 20          # 前序信息
+PRIORITY_ROLE = 30           # 角色规范
+PRIORITY_API = 40            # API 操作指令
+PRIORITY_CONSTRAINTS = 50    # 硬约束
+PRIORITY_EXTENSION = 60      # 扩展段
+
+
+# ---------------------------------------------------------------------------
+# PromptSection Protocol
+# ---------------------------------------------------------------------------
+@runtime_checkable
+class PromptSection(Protocol):
+    """一个 prompt 段"""
+
+    name: str                     # 段名（去重用，同名覆盖）
+    priority: int                 # 排序优先级（小数字=靠前）
+
+    def render(self, context: "PromptContext") -> str:
+        """渲染此段的文本内容。返回空字符串表示不注入。"""
+        ...
+
+    def should_include(self, context: "PromptContext") -> bool:
+        """是否注入此段（默认 True，条件段可覆盖）。"""
+        ...
+
+
+# ---------------------------------------------------------------------------
+# PromptContext 数据对象
+# ---------------------------------------------------------------------------
+@dataclass
+class PromptContext:
+    """Prompt 渲染的统一上下文"""
+
+    task_id: str
+    title: str
+    description: str
+    must_haves: str
+    project_id: str
+    agent_id: str
+
+    task: Optional[Dict] = None
+    role: str = "executor"
+    spawn_type: str = "executor"
+
+    # mail 专用
+    from_agent: str = ""
+    mail_type: str = ""          # inform / request
+
+    # toolchain 专用
+    event_type: str = ""         # ci_failure / review_request / ...
+    event_data: Dict = field(default_factory=dict)
+
+    # 前序产出
+    depends_on_outputs: Optional[List] = None
+
+
+# ---------------------------------------------------------------------------
+# PromptComposer 拼装器
+# ---------------------------------------------------------------------------
+class PromptComposer:
+    """有序拼装 prompt sections"""
+
+    SEPARATOR = "\n\n---\n\n"
+    TOKEN_BUDGET_WARN = 800      # token 预算警告阈值
+    CHARS_PER_TOKEN = 3.5        # 估算比率
+
+    def __init__(self) -> None:
+        self._sections: List[Any] = []  # List[PromptSection]
+
+    def add(self, section: Any) -> None:
+        """添加一个 section（同名覆盖）"""
+        self._sections = [s for s in self._sections if s.name != section.name]
+        self._sections.append(section)
+
+    def add_many(self, sections: List[Any]) -> None:
+        """批量添加"""
+        for s in sections:
+            self.add(s)
+
+    def compose(self, context: PromptContext) -> str:
+        """拼装最终 prompt
+
+        1. 过滤 should_include=False 的段
+        2. 按 priority 排序
+        3. 逐段 render
+        4. 过滤空段
+        5. 用分隔符连接
+        6. Token 预算警告（不截断）
+        """
+        active = [s for s in self._sections if s.should_include(context)]
+        active.sort(key=lambda s: s.priority)
+
+        parts = [s.render(context) for s in active]
+        parts = [p for p in parts if p.strip()]
+
+        result = self.SEPARATOR.join(parts)
+
+        # Token 估算
+        tokens = max(1, int(len(result) / self.CHARS_PER_TOKEN))
+        logger.debug(
+            "Composed prompt from %d sections, %d tokens",
+            len(parts), tokens,
+        )
+
+        if tokens > self.TOKEN_BUDGET_WARN:
+            logger.warning(
+                "Prompt exceeds %d token budget: %d tokens (task_id=%s)",
+                self.TOKEN_BUDGET_WARN, tokens, context.task_id,
+            )
+
+        return result