跨聊天、邮件与云文档统一检索,快速找回决策、资料和讨论记录
复制安装指令,让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "search" 技能: 1. 下载 https://raw.githubusercontent.com/anthropics/knowledge-work-plugins/main/enterprise-search/skills/search/SKILL.md 2. 保存为 ~/.claude/skills/search/SKILL.md 3. 装好后重载技能,告诉我可以用了
帮我找一下上个月讨论过的新版定价方案文档,可能在邮件、聊天记录或云盘里。
返回最相关的文档、相关对话来源,以及可帮助定位的摘要信息。
我们之前决定是否要把移动端改版延期?请帮我找到对应的讨论和最终结论。
整理出相关讨论记录、决策结论,以及出现这些信息的具体位置。
帮我找一下关于客户A投诉升级的那次沟通,可能在项目系统、邮件或团队聊天里。
给出最可能的沟通记录、涉及人员和时间线,便于快速继续跟进。
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Search across all connected MCP sources in a single query. Decompose the user's question, run parallel searches, and synthesize results.
Before searching, determine which MCP sources are available. Attempt to identify connected tools from the available tool list. Common sources:
If no MCP sources are connected:
To search across your tools, you'll need to connect at least one source.
Check your MCP settings to add ~~chat, ~~email, ~~cloud storage, or other tools.
Supported sources: ~~chat, ~~email, ~~cloud storage, ~~project tracker, ~~CRM, ~~knowledge base,
and any other MCP-connected service.
Analyze the search query to understand:
from: — Filter by sender/authorin: — Filter by channel, folder, or locationafter: — Only results after this datebefore: — Only results before this datetype: — Filter by content type (message, email, doc, thread, file)For each available source, create a targeted sub-query using that source's native search syntax:
~~chat:
from: maps to sender, in: maps to channel/room, dates map to time range filters~~email:
from: maps to sender, dates map to time range filterstype: to attachment filters or subject-line searches as appropriate~~cloud storage:
~~project tracker:
~~CRM:
~~knowledge base:
Run all sub-queries simultaneously across available sources. Do not wait for one source before searching another.
For each source:
Deduplication:
Ranking factors:
…
根据受众与汇报节奏生成清晰的项目进展与干系人更新
在分享分析结论前,检查方法、计算、偏差与结论是否可靠
生成人员规模、流失率、多元化与组织健康等人力分析报告
帮助识别、分类并排序技术债,明确重构与代码健康改进优先级。
帮助你为具体产品场景选择合适的 Zoom 能力层,并清晰说明技术取舍。
根据已批准内容简报,生成社媒设计、文案与发布排期并待你逐步审批。
帮助用户检索过往 Claude Code 对话,快速找回事实、决策与上下文线索。
通过语义检索项目文档,帮助 AI 编码前快速定位相关说明文件。
帮助用户检索 Markdown 知识库、笔记与文档,快速定位所需信息。
对存储在 Gemini FileSearchStores 的文档进行语义检索,并返回带来源引用的 AI 答案。
统一检索多类记忆源并生成排序摘要,帮助代理快速回忆上下文
将复杂问题拆解为多源检索策略,并汇总高相关结果与备选路径。