Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.
View on GitHubanthropics/knowledge-work-plugins
enterprise-search
February 2, 2026
Select agents to install to:
npx add-skill https://github.com/anthropics/knowledge-work-plugins/blob/main/enterprise-search/skills/search-strategy/SKILL.md -a claude-code --skill search-strategyInstallation paths:
.claude/skills/search-strategy/# Search Strategy > If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](../../CONNECTORS.md). The core intelligence behind enterprise search. Transforms a single natural language question into parallel, source-specific searches and produces ranked, deduplicated results. ## The Goal Turn this: ``` "What did we decide about the API migration timeline?" ``` Into targeted searches across every connected source: ``` ~~chat: "API migration timeline decision" (semantic) + "API migration" in:#engineering after:2025-01-01 ~~knowledge base: semantic search "API migration timeline decision" ~~project tracker: text search "API migration" in relevant workspace ``` Then synthesize the results into a single coherent answer. ## Query Decomposition ### Step 1: Identify Query Type Classify the user's question to determine search strategy: | Query Type | Example | Strategy | |-----------|---------|----------| | **Decision** | "What did we decide about X?" | Prioritize conversations (~~chat, email), look for conclusion signals | | **Status** | "What's the status of Project Y?" | Prioritize recent activity, task trackers, status updates | | **Document** | "Where's the spec for Z?" | Prioritize Drive, wiki, shared docs | | **Person** | "Who's working on X?" | Search task assignments, message authors, doc collaborators | | **Factual** | "What's our policy on X?" | Prioritize wiki, official docs, then confirmatory conversations | | **Temporal** | "When did X happen?" | Search with broad date range, look for timestamps | | **Exploratory** | "What do we know about X?" | Broad search across all sources, synthesize | ### Step 2: Extract Search Components From the query, extract: - **Keywords**: Core terms that must appear in results - **Entities**: People, projects, teams, tools (use memory system if available) - **Intent signals**: Decision words, status words, temporal markers - **Constraints**: Time ranges, source hints, author f