Airweave Search
Use this skill to effectively search and retrieve context from Airweave collections, whether answering questions or gathering context to complete tasks.
When to Search
Search when the user:
- Asks about data in their connected apps ("What did we discuss in Slack about...")
- Needs to find documents, messages, issues, or records
- Asks factual questions about their workspace ("Who is responsible for...", "What's our policy on...")
- References specific tools by name ("in Notion", "on GitHub", "in Jira")
- Needs recent information you don't have in your training
- Needs you to check app data for context to complete a task ("check our Notion docs", "look at the Jira ticket", "see what we decided in Slack")
Don't search when:
- User asks general knowledge questions (use your training)
- User is asking how to SET UP Airweave (use
airweave-setupskill instead) - User already provided all needed context in the conversation
- The question is about Airweave itself, not data within it
Search Modes
Airweave provides three search modes. Choose based on user intent:
| Mode | When to Use | Speed |
|---|---|---|
instant | Simple lookups, exact term matching, browsing | Fastest |
classic | Most searches — AI generates an optimized search plan | Fast |
agentic | Complex questions requiring reasoning, multi-step retrieval | Slower, highest quality |
Mode Selection Guide
| User Intent | Mode |
|---|---|
| Quick document lookup | instant |
| Finding specific information | classic (default) |
| General topic exploration | classic |
| "Summarize", "analyze", "compare" | agentic |
| Complex multi-source questions | agentic |
| Simple keyword search | instant with retrieval_strategy: "keyword" |
Query Formulation
Extract Key Concepts
Turn user intent into effective search queries:
| User Says | Search Query |
|---|---|
| "What did Sarah say about the launch?" | "Sarah product launch" |
| "Find the API documentation" | "API documentation" |
| "Any bugs reported this week?" | "bug report issues" |
| "What's our refund policy?" | "refund policy customer" |
Query Tips
- Use natural language - Airweave uses semantic search, not keyword matching
- Include context - "pricing feedback" is better than just "pricing"
- Be specific but not too narrow - Start moderately specific, broaden if no results
- Avoid filler words - Skip "please find", "can you search for"
Parameter Quick Reference
| Parameter | Values | When to Use |
|---|---|---|
mode | instant/classic/agentic | instant for speed, classic for most searches, agentic for complex reasoning |
limit | 1-1000 | Lower (5-10) for quick answers, higher (20-50) for exploration |
offset | 0+ | Pagination (instant/classic only) |
retrieval_strategy | hybrid/neural/keyword | Instant mode only: keyword for exact terms, neural for concepts, hybrid (default) for both |
thinking | boolean | Agentic mode only: enable extended reasoning for complex queries |
See PARAMETERS.md for detailed guidance.
Handling Results
Interpreting Scores
Results include a relevance_score field:
| Score | Meaning | Action |
|---|---|---|
| 0.85+ | Highly relevant | Use confidently |
| 0.70-0.85 | Likely relevant | Use with context |
| 0.50-0.70 | Possibly relevant | Mention uncertainty |
| Below 0.50 | Weak match | Consider rephrasing query |
Understanding Result Structure
Each result contains:
name— Document/entity titletextual_representation— The full text contentbreadcrumbs— Hierarchy path (e.g., Workspace > Channel > Message)airweave_system_metadata.source_name— Source app (e.g., "Slack", "Notion")web_url— Link back to the original itemcreated_at/updated_at— Timestamps
Synthesizing Answers
When presenting results to users:
- Lead with the answer - Don't start with "I found 5 results"
- Cite sources - Mention where info came from ("According to your Slack conversation...")
- Use breadcrumbs - Reference the hierarchy path for context ("In the Engineering > API Design channel...")
- Synthesize, don't dump - Combine relevant parts into coherent response
- Acknowledge gaps - If results don't fully answer, say so
Handling No/Poor Results
If search returns no results or low-quality matches:
- Try a different mode - Switch from
instanttoclassic, orclassictoagentic - Broaden the query - Remove specific terms, use more general concepts
- Try different phrasing - Rephrase using synonyms or related terms
- Increase limit - Fetch more results to find relevant matches
- Check source availability - The data source might not be connected
- Ask for clarification - User might have more context to share
Finding the Search Tool
Airweave MCP tools follow the naming pattern search-{collection-name}. Look for tools matching this pattern in your available MCP tools.
Examples:
search-acmes-slack-k8v2x1search-acmes-notion-p3m9q7search-acmes-jira-w5n4r2
If no Airweave search tool is available:
- The user may not have Airweave MCP configured
- Ask if they have Airweave set up and connected to their AI assistant
- Suggest using the
airweave-setupskill for configuration help
Multiple collections: If multiple search-* tools are available, choose based on the collection name and the user's request. If unclear which to use, ask the user or try the most general-sounding one first.
Calling the Search Tool
Use the search-{collection} MCP tool with your chosen parameters:
search-acmes-slack-k8v2x1({
query: "customer feedback pricing",
mode: "classic",
limit: 10
})search-acmes-notion-p3m9q7({
query: "API authentication docs",
mode: "instant",
retrieval_strategy: "hybrid"
})search-acmes-jira-w5n4r2({
query: "What decisions were made about the refund policy?",
mode: "agentic"
})Examples
See EXAMPLES.md for complete conversation examples showing effective search patterns.