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 filters - **Negations**: Things to exclude

### Step 3: Generate Sub-Queries Per Source

For each available source, create one or more targeted queries:

**Prefer semantic search** for: - Conceptual questions ("What do we think about...") - Questions where exact keywords are unknown - Exploratory queries

**Prefer keyword search** for: - Known terms, project names, acronyms - Exact phrases the user quoted - Filter-heavy queries (from:, in:, after:)

**Generate multiple query variants** when the topic might be referred to differently: ``` User: "Kubernetes setup" Queries: "Kubernetes", "k8s", "cluster", "container orchestration" ```

## Source-Specific Query Translation

### ~~chat

**Semantic search** (natural language questions): ``` query: "What is the status of project aurora?" ```

**Keyword search:** ``` query: "project aurora status update" query: "aurora in:#engineering after:2025-01-15" query: "from:<@UserID> aurora" ```

**Filter mapping:** | Enterprise filter | ~~chat syntax | |------------------|--------------| | `from:sarah` | `from:sarah` or `from:<@USERID>` | | `in:engineering` | `in:engineering` | | `after:2025-01-01` | `after:2025-01-01` | | `before:2025-02-01` | `before:2025-02-01` | | `type:thread` | `is:thread` | | `type:file` | `has:file` |

### ~~knowledge base (Wiki)

**Semantic search** — Use for conceptual queries: ``` descriptive_query: "API migration timeline and decision rationale" ```

**Keyword search** — Use for exact terms: ``` query: "API migration" query: "\"API migration timeline\"" (exact phrase) ```

### ~~project tracker

**Task search:** ``` text: "API migration" workspace: [workspace_id] completed: false (for status queries) assignee_any: "me" (for "my tasks" queries) ```

**Filter mapping:** | Enterprise filter | ~~project tracker parameter | |------------------|----------------| | `from:sarah` | `assignee_any` or `created_by_any` | | `after:2025-01-01` | `modified_on_after: "2025-01-01"` | | `type:milestone` | `resource_subtype: "milestone"` |

## Result Ranking

### Relevance Scoring

Score each result on these factors (weighted by query type):

| Factor | Weight (Decision) | Weight (Status) | Weight (Document) | Weight (Factual) | |--------|-------------------|------------------|--------------------|-------------------| | Keyword match | 0.3 | 0.2 | 0.4 | 0.3 | | Freshness | 0.3 | 0.4 | 0.2 | 0.1 | | Authority | 0.2 | 0.1 | 0.3 | 0.4 | | Completeness | 0.2 | 0.3 | 0.1 | 0.2 |

### Authority Hierarchy

Depends on query type:

**For factual/policy questions:** ``` Wiki/Official docs > Shared documents > Email announcements > Chat messages ```

**For "what happened" / decision questions:** ``` Meeting notes > Thread conclusions > Email confirmations > Chat messages ```

**For status questions:** ``` Task tracker > Recent chat > Status docs > Email updates ```

## Handling Ambiguity

When a query is ambiguous, prefer asking one focused clarifying question over guessing:

``` Ambiguous: "search for the mig