fix(skills): 修复 skills 加载以及按需暴露问题，并新增 reporter 技能，已可以替代数据库报表智能体
This commit is contained in:
Wenjie Zhang
parent
96ce4dbe8a
commit
186012e5e8
@ -93,7 +93,7 @@ class BaseContext:
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metadata={
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"name": "Skills",
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"options": [],
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"description": "可选技能列表（由超级管理员维护）。运行时仅挂载并只读暴露选中的 skills。",
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"description": "可选技能列表（由超级管理员维护）。运行时仅挂载并只读暴露选中的 skills。技能依赖的工具和 MCP 服务器也会被自动挂载。",
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"type": "list",
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},
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)
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@ -13,6 +13,7 @@ from langchain.tools.tool_node import ToolCallRequest
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from langgraph.types import Command
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from sqlalchemy.ext.asyncio import AsyncSession
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from src.agents.common.toolkits import get_all_tool_instances
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from src.repositories.skill_repository import SkillRepository
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from src.services.mcp_service import get_enabled_mcp_tools
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from src.services.skill_service import _normalize_string_list, is_valid_skill_slug
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@ -171,6 +172,21 @@ class SkillsMiddleware(AgentMiddleware):
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self.skills_context_name = skills_context_name
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self.enable_skills_prompt = enable_skills_prompt
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self.skills_sources_for_prompt = skills_sources_for_prompt or ["/skills/"]
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# 实例级缓存：避免每次模型调用都查数据库
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self._dependency_map_cache: dict[str, SkillDependencyNode] | None = None
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self._prompt_metadata_cache: dict[str, SkillPromptMetadata] | None = None
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async def _get_dependency_map_cached(self) -> dict[str, SkillDependencyNode]:
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"""获取依赖映射（带缓存）"""
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if self._dependency_map_cache is None:
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self._dependency_map_cache = await get_dependency_map()
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return self._dependency_map_cache
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async def _get_prompt_metadata_cached(self) -> dict[str, SkillPromptMetadata]:
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"""获取提示词元数据（带缓存）"""
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if self._prompt_metadata_cache is None:
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self._prompt_metadata_cache = await get_prompt_metadata()
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return self._prompt_metadata_cache
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async def abefore_agent(self, state: SkillsState, runtime) -> dict[str, Any] | None:
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"""在 agent 执行前注入 skills 提示词"""
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@ -182,8 +198,8 @@ class SkillsMiddleware(AgentMiddleware):
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if getattr(runtime_context, "_skills_prompt_injected", False):
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return None
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# 从数据库加载 skills 数据
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dependency_map = await get_dependency_map()
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# 从数据库加载 skills 数据（使用缓存）
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dependency_map = await self._get_dependency_map_cached()
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# 获取配置的 skills
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configured_skills = getattr(runtime_context, self.skills_context_name, None) or []
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@ -219,8 +235,8 @@ class SkillsMiddleware(AgentMiddleware):
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"""包装模型调用，处理动态激活和依赖展开"""
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runtime_context = request.runtime.context
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# 从数据库加载 skills 数据
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dependency_map = await get_dependency_map()
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# 从缓存加载 skills 数据
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dependency_map = await self._get_dependency_map_cached()
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# 1. 获取配置的 skills
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configured_skills = getattr(runtime_context, self.skills_context_name, None) or []
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@ -239,40 +255,47 @@ class SkillsMiddleware(AgentMiddleware):
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# 4. 更新 runtime_context 中的 visible_skills
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setattr(runtime_context, "_visible_skills", visible_skills)
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# 5. 构建依赖包
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deps_bundle = await self._build_dependency_bundle(visible_skills)
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# 5. 构建依赖包（只从直接激活的 skills 获取依赖，不包含闭包展开的依赖）
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deps_bundle = await self._build_dependency_bundle(activated)
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# 6. 加载依赖的工具
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if deps_bundle["tools"] or deps_bundle["mcps"]:
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enabled_tools = await self._get_tools_from_context(
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# 6. 加载依赖的工具（普通工具 + MCP 工具）
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enabled_tools = []
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# 6.1 从 toolkits 获取普通工具
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if deps_bundle["tools"]:
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all_tools = get_all_tool_instances()
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required_tool_names = set(deps_bundle["tools"])
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enabled_tools = [t for t in all_tools if t.name in required_tool_names]
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# 6.2 获取 MCP 工具
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if deps_bundle["mcps"]:
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mcp_tools = await self._get_mcp_tools_from_context(
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runtime_context,
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extra_tool_names=deps_bundle["tools"],
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extra_mcps=deps_bundle["mcps"],
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)
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enabled_tools.extend(mcp_tools)
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# 合并工具
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if enabled_tools:
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existing_tools = list(request.tools or [])
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enabled_tool_names = {t.name for t in enabled_tools}
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merged_tools = []
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for t_bind in existing_tools:
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if t_bind.name in enabled_tool_names:
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merged_tools.append(t_bind)
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if merged_tools:
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request = request.override(tools=merged_tools)
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# 合并工具：保留原有工具 + 追加依赖的新工具
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if enabled_tools:
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existing_tool_names = {t.name for t in request.tools or []}
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merged_tools = list(request.tools or [])
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for t in enabled_tools:
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if t.name not in existing_tool_names:
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merged_tools.append(t)
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request = request.override(tools=merged_tools)
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return await handler(request)
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async def _build_dependency_bundle(self, visible_skills: list[str]) -> dict[str, list[str]]:
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"""根据 visible_skills 构建依赖包"""
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dependency_map = await get_dependency_map()
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async def _build_dependency_bundle(self, activated_skills: list[str]) -> dict[str, list[str]]:
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"""根据直接激活的 skills 构建依赖包（不包含闭包展开的依赖）"""
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dependency_map = await self._get_dependency_map_cached()
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tools: list[str] = []
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mcps: list[str] = []
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seen_tools: set[str] = set()
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seen_mcps: set[str] = set()
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for slug in visible_skills:
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for slug in activated_skills:
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dep = dependency_map.get(slug, {})
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for tool_name in dep.get("tools", []):
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if tool_name in seen_tools:
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@ -285,11 +308,11 @@ class SkillsMiddleware(AgentMiddleware):
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seen_mcps.add(mcp_name)
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mcps.append(mcp_name)
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return {"tools": tools, "mcps": mcps, "skills": visible_skills}
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return {"tools": tools, "mcps": mcps, "skills": activated_skills}
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async def _collect_prompt_metadata(self, slugs: list[str]) -> list[SkillPromptMetadata]:
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"""收集指定 slugs 的提示词元数据"""
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prompt_metadata = await get_prompt_metadata()
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prompt_metadata = await self._get_prompt_metadata_cached()
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result: list[SkillPromptMetadata] = []
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seen: set[str] = set()
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@ -310,28 +333,16 @@ class SkillsMiddleware(AgentMiddleware):
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return result
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async def _get_tools_from_context(
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async def _get_mcp_tools_from_context(
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self,
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context,
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*,
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extra_tool_names: list[str] | None = None,
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extra_mcps: list[str] | None = None,
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) -> list:
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"""从上下文配置中获取工具列表"""
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"""从上下文配置中获取 MCP 工具列表"""
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import asyncio
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selected_tools = []
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# 1. 工具（从 extra_tool_names 获取）
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all_tool_names: list[str] = []
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for tool_name in extra_tool_names or []:
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if isinstance(tool_name, str):
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all_tool_names.append(tool_name)
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# 这里简化处理：假设工具已经在其他 middleware 中加载
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# SkillsMiddleware 主要负责 MCP 工具的加载
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# 2. MCP 工具（并行加载）
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# MCP 工具（并行加载）
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mcps = getattr(context, "mcps", None) or []
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all_mcp_names: list[str] = []
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for server_name in mcps:
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@ -357,6 +368,7 @@ class SkillsMiddleware(AgentMiddleware):
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# 并行加载所有 MCP 工具
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results = await asyncio.gather(*[load_mcp_tools(name) for name in unique_mcp_names])
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selected_tools = []
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for tools in results:
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selected_tools.extend(tools)
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@ -46,18 +46,12 @@ def get_connection_manager() -> MySQLConnectionManager:
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return _connection_manager
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class TableListModel(BaseModel):
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"""获取表名列表的参数模型"""
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pass
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@tool(
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category="mysql",
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tags=["数据库", "查询"],
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display_name="列出MySQL表",
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name_or_callable="mysql_list_tables",
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args_schema=TableListModel,
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)
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def mysql_list_tables() -> str:
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"""【查询表名及说明】获取数据库中的所有表名
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28
src/agents/skills/reporter/SKILLS.md
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28
src/agents/skills/reporter/SKILLS.md
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@ -0,0 +1,28 @@
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---
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name: sql-reporter
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description: "生成 SQL 查询报表并生成可视化图表。当用户需要查询数据库并以报表形式展示结果时使用此技能，包括：统计销售数据、分析用户行为、生成业务报表、查询业务指标等。"
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---
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# SQL 报表技能
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根据用户的指令，使用数据库工具和图表绘制工具，构建 SQL 查询报告。
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## 操作流程
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1. 理解用户的指令，明确报表的需求和目标
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2. 使用 MySQL 工具生成正确的 SQL 查询
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3. 执行查询并获取结果
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4. 使用 Charts MCP 生成图表
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5. 将图表以 markdown 图片格式嵌入报表
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## 关键约束
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- 生成的 SQL 查询必须正确且高效，避免全表扫描
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- 图表生成工具的返回结果不会默认渲染，必须在最终报表中以 `` 格式嵌入
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- 只返回报表相关的结论，不要返回原始 SQL 查询语句
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## 允许的工具
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- MySQL 工具：执行 SQL 查询
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- Charts MCP：生成可视化图表
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- 网络检索工具：必要时补充背景信息
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