/notion-research-documentation

Advanced Search Techniques

Search Filtering

By Date Range

Use created_date_range to find recent content:

filters: {
  created_date_range: {
    start_date: "2024-01-01",
    end_date: "2025-01-01"
  }
}

When to use:

• Finding recent updates on a topic
• Focusing on current information
• Excluding outdated content

By Creator

Use created_by_user_ids to find content from specific people:

filters: {
  created_by_user_ids: ["user-id-1", "user-id-2"]
}

When to use:

• Research from subject matter experts
• Team-specific information
• Attribution tracking

Combined Filters

Stack filters for precision:

filters: {
  created_date_range: {
    start_date: "2024-10-01"
  },
  created_by_user_ids: ["expert-user-id"]
}

Scoped Searches

Teamspace Scoping

Restrict search to specific teamspace:

teamspace_id: "teamspace-uuid"

When to use:

• Project-specific research
• Department-focused information
• Reducing noise from irrelevant results

Page Scoping

Search within a specific page and its subpages:

page_url: "https://notion.so/workspace/Page-Title-uuid"

When to use:

• Research within a project hierarchy
• Documentation updates
• Focused investigation

Database Scoping

Search within a database's content:

data_source_url: "collection://data-source-uuid"

When to use:

• Task/project database research
• Structured data investigation
• Finding specific entries

Search Strategies

Broad to Narrow

1. Start with general search term
2. Review results for relevant teamspaces/pages
3. Re-search with scope filters
4. Fetch detailed content from top results

Example:

Search 1: query="API integration" → 50 results across workspace
Search 2: query="API integration", teamspace_id="engineering" → 12 results
Fetch: Top 3-5 most relevant pages

Multi-Query Approach

Run parallel searches with related terms:

Query 1: "API integration"
Query 2: "API authentication"
Query 3: "API documentation"

Combine results to build comprehensive picture.

Temporal Research

Search across time periods to track evolution:

Search 1: created_date_range 2023 → Historical context
Search 2: created_date_range 2024 → Recent developments
Search 3: created_date_range 2025 → Current state

Result Processing

Identifying Relevant Results

Look for:

• High semantic match: Result summary closely matches query intent
• Recent updates: Last-edited date is recent
• Authoritative sources: Created by known experts or in official locations
• Comprehensive content: Result summary suggests detailed information

Prioritizing Fetches

Fetch pages in order of relevance:

1. Primary sources: Direct documentation, official pages
2. Recent updates: Newly edited content
3. Related context: Supporting information
4. Historical reference: Background and context

Don't fetch everything - be selective based on research needs.

Handling Too Many Results

If search returns 20+ results:

1. Add filters: Narrow by date, creator, or teamspace
2. Refine query: Use more specific terms
3. Use page scoping: Search within relevant parent page
4. Sample strategically: Fetch diverse results (recent, popular, authoritative)

Handling Too Few Results

If search returns < 3 results:

1. Broaden query: Use more general terms
2. Remove filters: Search full workspace
3. Try synonyms: Alternative terminology
4. Search in related areas: Adjacent teamspaces or pages

Search Quality

Effective Search Queries

Good queries (specific, semantic):

• "Q4 product roadmap"
• "authentication implementation guide"
• "customer feedback themes"

Weak queries (too vague):

• "roadmap"
• "guide"
• "feedback"

Over-specific queries (too narrow):

• "Q4 2024 product roadmap for mobile app version 3.2 feature X"

User Context

Always use available user context:

• Query should match their terminology
• Scope to their relevant teamspaces
• Consider their role/department
• Reference their recent pages

Connected Sources

Notion Integrations

Search extends beyond Notion pages to:

• Slack messages (if connected)
• Google Drive documents (if connected)
• GitHub issues/PRs (if connected)
• Jira tickets (if connected)

Be aware results may come from these sources.

Source Attribution

When citing results from connected sources:

• Note the source type in documentation
• Use appropriate mention format
• Verify user has access to the source system