Imported skill advanced_search from openai
Scanned 9/11/2026
Install to Claude Code
npx -y skills add bitwikiorg/skills.md --skill advanced_search --agent claude-codeInstalls into .claude/skills of the current project.
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---
description: Imported skill advanced_search from openai
name: advanced_search
signature: f9c70a3b731ce76f35aee7caa53888cc8b22dadc17dd0f54cce95933a0cbbe91
source: /a0/tmp/skills_research/openai/skills/.curated/notion-research-documentation/reference/advanced-search.md
---
# 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- Excluding outdated content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
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