Search Strategy

Multi-Source Search Strategy

Plan, execute, and refine search strategies for complex enterprise queries that span multiple tools and require iterative refinement.

Strategy Planning Process

Step 1: Analyze the Query

Break down the user's question into searchable components:

Step 2: Select Target Sources

Evaluate which sources are most likely to contain relevant results:

Source selection matrix:

Step 3: Formulate Sub-Queries

Transform the original query into source-specific sub-queries:

Original: "Why did we switch from Redis to DynamoDB for session storage?"

Sub-queries:
1. Wiki     → "session storage" OR "DynamoDB" OR "Redis migration"
2. Docs     → "session" AND ("DynamoDB" OR "Redis") — type:proposal OR type:design-doc
3. Email    → "session storage" OR "Redis replacement" — from:engineering-leads
4. Chat     → "DynamoDB sessions" OR "Redis sessions" — channels:#backend,#architecture
5. Tickets  → labels:infrastructure "session" AND ("Redis" OR "DynamoDB")
6. Code     → path:*session* OR path:*config* "dynamodb" — recent commits

Step 4: Define Execution Plan

# Search Execution Plan

## Query: [original query]
## Decomposition:
- Concept A: [term variations and synonyms]
- Concept B: [term variations and synonyms]
- Filter: [time range, people, teams]

## Execution Order:
1. [High-priority source] — [specific query] — Expected: [what we hope to find]
2. [Medium-priority source] — [specific query] — Expected: [what we hope to find]
3. [Lower-priority source] — [specific query] — Expected: [what we hope to find]

## Refinement Triggers:
- If Step 1 finds [X], narrow Step 2 to [Y]
- If Step 1 finds nothing, broaden Step 2 to [Z]
- If conflicting results, add Step 4: [verification query]

Step 5: Execute and Merge Results

Result Ranking Framework

Score each result on four dimensions:

Composite score: (Relevance * 0.4) + (Authority * 0.25) + (Recency * 0.2) + (Uniqueness * 0.15)

Output Format

# Search Strategy Report
Query: [original question]
Sources searched: [N] | Results found: [N] | Top results: [N]

## Search Plan Executed
| Step | Source   | Query Used                    | Results |
|------|----------|-------------------------------|---------|
| 1    | [Source] | [query]                       | [N]     |
| 2    | [Source] | [query]                       | [N]     |

## Top Results (Ranked)
### 1. [Result Title] — [Source] — Score: [X/10]
- **Relevance**: [why this matches]
- **Key excerpt**: "[relevant quote]"
- **Date**: [date] | **Author**: [author]

### 2. [Result Title] — [Source] — Score: [X/10]
- **Relevance**: [why this matches]
- **Key excerpt**: "[relevant quote]"
- **Date**: [date] | **Author**: [author]

## Answer Summary
[Synthesized answer based on top results]

## Search Refinement Suggestions
- To find more: try [broader query suggestion]
- To narrow down: add [filter suggestion]
- Unexplored sources: [sources not yet queried and why they might help]

Query Optimization Techniques

Iterative Refinement

After initial results, determine if refinement is needed:

• Too many results (>50): Add filters, use phrase matching, narrow date range
• Too few results (<3): Expand synonyms, broaden date range, add sources
• Wrong results: Analyze why results are off-topic, add negative filters
• Partial answer: Identify the gap and formulate a targeted follow-up query

Edge Cases

• Ambiguous queries: Ask the user to clarify before executing; present 2-3 interpretations
• No results anywhere: Suggest the information may not exist in connected sources; recommend who to ask
• Cross-language content: Note if sources contain content in multiple languages; expand queries accordingly
• Acronyms and jargon: Expand acronyms in queries and search for both forms
• Stale indexes: If a source's index is known to be delayed, warn about potential missing recent items

Quality Checklist

• Query decomposed into at least 2 sub-queries
• At least 3 sources considered
• Results ranked by composite score
• Conflicting information flagged
• Knowledge gaps identified
• Refinement suggestions provided