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Search Command

搜索命令

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.
如果你看到不熟悉的占位符或需要查看已连接的工具，请参阅CONNECTORS.md。
通过单个查询即可搜索所有已连接的MCP数据源。分解用户的问题，运行并行搜索，并合成结果。

Instructions

操作说明

1. Check Available Sources

1. 检查可用数据源

Before searching, determine which MCP sources are available. Attempt to identify connected tools from the available tool list. Common sources:
  • ~~chat — chat platform tools
  • ~~email — email tools
  • ~~cloud storage — cloud storage tools
  • ~~project tracker — project tracking tools
  • ~~CRM — CRM tools
  • ~~knowledge base — knowledge base tools
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.
在搜索前，确定哪些MCP数据源可用。尝试从可用工具列表中识别已连接的工具。常见数据源：
  • ~~chat — 聊天平台工具
  • ~~email — 邮箱工具
  • ~~cloud storage — 云存储工具
  • ~~project tracker — 项目追踪工具
  • ~~CRM — CRM工具
  • ~~knowledge base — 知识库工具
如果没有连接任何MCP数据源：
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.

2. Parse the User's Query

2. 解析用户查询

Analyze the search query to understand:
  • Intent: What is the user looking for? (a decision, a document, a person, a status update, a conversation)
  • Entities: People, projects, teams, tools mentioned
  • Time constraints: Recency signals ("this week", "last month", specific dates)
  • Source hints: References to specific tools ("in ~~chat", "that email", "the doc")
  • Filters: Extract explicit filters from the query: 
    • from:
      — Filter by sender/author
    • in:
      — Filter by channel, folder, or location
    • after:
      — Only results after this date
    • before:
      — Only results before this date
    • type:
      — Filter by content type (message, email, doc, thread, file)
分析搜索查询，明确以下信息：
  • 意图：用户要找什么？（决策、文档、人员、状态更新、对话）
  • 实体：提及的人员、项目、团队、工具
  • 时间限制：时效性信号（“本周”、“上个月”、具体日期）
  • 数据源提示：对特定工具的引用（“在~~chat中”、“那封邮件”、“该文档”）
  • 筛选条件：从查询中提取明确的筛选器： 
    • from:
      — 按发送者/作者筛选
    • in:
      — 按频道、文件夹或位置筛选
    • after:
      — 仅显示该日期之后的结果
    • before:
      — 仅显示该日期之前的结果
    • type:
      — 按内容类型筛选（消息、邮件、文档、线程、文件）

3. Decompose into Sub-Queries

3. 分解为子查询

For each available source, create a targeted sub-query using that source's native search syntax:
~~chat:
  • Use available search and read tools for your chat platform
  • Translate filters: 
    from:
    maps to sender, 
    in:
    maps to channel/room, dates map to time range filters
  • Use natural language queries for semantic search when appropriate
  • Use keyword queries for exact matches
~~email:
  • Use available email search tools
  • Translate filters: 
    from:
    maps to sender, dates map to time range filters
  • Map 
    type:
    to attachment filters or subject-line searches as appropriate
~~cloud storage:
  • Use available file search tools
  • Translate to file query syntax: name contains, full text contains, modified date, file type
  • Consider both file names and content
~~project tracker:
  • Use available task search or typeahead tools
  • Map to task text search, assignee filters, date filters, project filters
~~CRM:
  • Use available CRM query tools
  • Search across Account, Contact, Opportunity, and other relevant objects
~~knowledge base:
  • Use semantic search for conceptual questions
  • Use keyword search for exact matches
针对每个可用数据源，使用该数据源的原生搜索语法创建针对性的子查询：
~~chat:
  • 使用聊天平台提供的搜索和读取工具
  • 转换筛选条件：
    from:
    对应发送者，
    in:
    对应频道/房间，日期对应时间范围筛选器
  • 适当时使用自然语言查询进行语义搜索
  • 使用关键词查询进行精确匹配
~~email:
  • 使用可用的邮箱搜索工具
  • 转换筛选条件：
    from:
    对应发送者，日期对应时间范围筛选器
  • 根据情况将
    type:
    映射为附件筛选或主题行搜索
~~cloud storage:
  • 使用可用的文件搜索工具
  • 转换为文件查询语法：名称包含、全文包含、修改日期、文件类型
  • 同时考虑文件名和文件内容
~~project tracker:
  • 使用可用的任务搜索或预输入工具
  • 映射为任务文本搜索、经办人筛选、日期筛选、项目筛选
~~CRM:
  • 使用可用的CRM查询工具
  • 在客户、联系人、商机及其他相关对象中进行搜索
~~knowledge base:
  • 针对概念性问题使用语义搜索
  • 针对精确匹配使用关键词搜索

4. Execute Searches in Parallel

4. 并行执行搜索

Run all sub-queries simultaneously across available sources. Do not wait for one source before searching another.
For each source:
  • Execute the translated query
  • Capture results with metadata (timestamps, authors, links, source type)
  • Note any sources that fail or return errors — do not let one failure block others
在所有可用数据源上同时运行所有子查询。不要等待一个数据源搜索完成后再进行另一个。
针对每个数据源：
  • 执行转换后的查询
  • 捕获包含元数据（时间戳、作者、链接、数据源类型）的结果
  • 记录任何搜索失败或返回错误的数据源 — 不要因一个数据源失败而阻塞其他数据源

5. Rank and Deduplicate Results

5. 排序与去重

Deduplication:
  • Identify the same information appearing across sources (e.g., a decision discussed in ~~chat AND confirmed via email)
  • Group related results together rather than showing duplicates
  • Prefer the most authoritative or complete version
Ranking factors:
  • Relevance: How well does the result match the query intent?
  • Freshness: More recent results rank higher for status/decision queries
  • Authority: Official docs > wiki > chat messages for factual questions; conversations > docs for "what did we discuss" queries
  • Completeness: Results with more context rank higher
去重：
  • 识别在多个数据源中出现的相同信息（例如，在~~chat中讨论的决策同时通过邮件确认）
  • 将相关结果分组，而非显示重复项
  • 优先选择最权威或最完整的版本
排序因素：
  • 相关性：结果与查询意图的匹配程度如何？
  • 时效性：对于状态/决策类查询，较新的结果排名更高
  • 权威性：对于事实性问题，官方文档 > 维基 > 聊天消息；对于“我们讨论了什么”类查询，对话 > 文档
  • 完整性：包含更多上下文的结果排名更高

6. Present Unified Results

6. 呈现统一结果

Format the response as a synthesized answer, not a raw list of results:
For factual/decision queries:
[Direct answer to the question]

Sources:
- [Source 1: brief description] (~~chat, #channel, date)
- [Source 2: brief description] (~~email, from person, date)
- [Source 3: brief description] (~~cloud storage, doc name, last modified)
For exploratory queries ("what do we know about X"):
[Synthesized summary combining information from all sources]

Found across:
- ~~chat: X relevant messages in Y channels
- ~~email: X relevant threads
- ~~cloud storage: X related documents
- [Other sources as applicable]

Key sources:
- [Most important source with link/reference]
- [Second most important source]
For "find" queries (looking for a specific thing):
[The thing they're looking for, with direct reference]

Also found:
- [Related items from other sources]
将响应格式化为合成后的答案，而非原始结果列表：
针对事实/决策类查询：
[Direct answer to the question]

Sources:
- [Source 1: brief description] (~~chat, #channel, date)
- [Source 2: brief description] (~~email, from person, date)
- [Source 3: brief description] (~~cloud storage, doc name, last modified)
针对探索性查询（“我们对X了解多少”）：
[Synthesized summary combining information from all sources]

Found across:
- ~~chat: X relevant messages in Y channels
- ~~email: X relevant threads
- ~~cloud storage: X related documents
- [Other sources as applicable]

Key sources:
- [Most important source with link/reference]
- [Second most important source]
针对“查找”类查询（寻找特定内容）：
[The thing they're looking for, with direct reference]

Also found:
- [Related items from other sources]

7. Handle Edge Cases

7. 处理边缘情况

Ambiguous queries: If the query could mean multiple things, ask one clarifying question before searching:
"API redesign" could refer to a few things. Are you looking for:
1. The REST API v2 redesign (Project Aurora)
2. The internal SDK API changes
3. Something else?
No results:
I couldn't find anything matching "[query]" across [list of sources searched].

Try:
- Broader terms (e.g., "database" instead of "PostgreSQL migration")
- Different time range (currently searching [time range])
- Checking if the relevant source is connected (currently searching: [sources])
Partial results (some sources failed):
[Results from successful sources]

Note: I couldn't reach [failed source(s)] during this search.
Results above are from [successful sources] only.
模糊查询： 如果查询存在多种含义，在搜索前先提出一个澄清问题：
"API redesign" could refer to a few things. Are you looking for:
1. The REST API v2 redesign (Project Aurora)
2. The internal SDK API changes
3. Something else?
无结果：
I couldn't find anything matching "[query]" across [list of sources searched].

Try:
- Broader terms (e.g., "database" instead of "PostgreSQL migration")
- Different time range (currently searching [time range])
- Checking if the relevant source is connected (currently searching: [sources])
部分结果（部分数据源搜索失败）：
[Results from successful sources]

Note: I couldn't reach [failed source(s)] during this search.
Results above are from [successful sources] only.

Notes

注意事项

  • Always search multiple sources in parallel — never sequentially
  • Synthesize results into answers, do not just list raw search results
  • Include source attribution so users can dig deeper
  • Respect the user's filter syntax and apply it appropriately per source
  • When a query mentions a specific person, search for their messages/docs/mentions across all sources
  • For time-sensitive queries, prioritize recency in ranking
  • If only one source is connected, still provide useful results from that source
  • 始终并行搜索多个数据源 — 绝不要按顺序搜索
  • 将结果合成为答案，不要仅列出原始搜索结果
  • 包含数据源归属信息，方便用户深入查看
  • 尊重用户的筛选语法，并针对每个数据源适当应用
  • 当查询提及特定人员时，在所有数据源中搜索他们的消息/文档/提及内容
  • 针对时效性强的查询，在排序时优先考虑时效性
  • 如果仅连接了一个数据源，仍需提供该数据源中的有用结果