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-setup skill instead)
• User already provided all needed context in the conversation
• The question is about Airweave itself, not data within it

Query Formulation

Extract Key Concepts

Turn user intent into effective search queries:

Query Tips

1. Use natural language – Airweave uses semantic search, not keyword matching
2. Include context – “pricing feedback” is better than just “pricing”
3. Be specific but not too narrow – Start moderately specific, broaden if no results
4. Avoid filler words – Skip “please find”, “can you search for”

Parameter Selection

Choose parameters based on user intent:

Parameter Quick Reference

See PARAMETERS.md for detailed guidance.

Handling Results

Interpreting Scores

Synthesizing Answers

When presenting results to users:

1. Lead with the answer – Don’t start with “I found 5 results”
2. Cite sources – Mention where info came from (“According to your Slack conversation…”)
3. Synthesize, don’t dump – Combine relevant parts into coherent response
4. Acknowledge gaps – If results don’t fully answer, say so

Handling No/Poor Results

If search returns no results or low-quality matches:

1. Broaden the query – Remove specific terms, use more general concepts
2. Try different phrasing – Rephrase using synonyms or related terms
3. Increase limit – Fetch more results to find relevant matches
4. Check source availability – The data source might not be connected
5. 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-k8v2x1
• search-acmes-notion-p3m9q7
• search-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-setup skill 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",
  recency_bias: 0.7,
  limit: 10
})

search-acmes-notion-p3m9q7({
  query: "API authentication docs",
  search_method: "hybrid",
  enable_reranking: true
})

search-acmes-jira-w5n4r2({
  query: "What is our refund policy?",
  response_type: "completion"
})

Examples

See EXAMPLES.md for complete conversation examples showing effective search patterns.