search-notes

Also use when:

• Unsure how to proceed
• Working with internal services, products, or processes
• Knowledge required is not publicly available
• The task relates to a specific repo, environment, or system

Treat this skill as:

Your internal memory lookup

What this skill does

Performs a hybrid search (dense + sparse) over stored notes.

Uses the Qdrant MCP server via the qdrant-search-notes tool.

The tool performs:

• Dense semantic search
• Sparse keyword search
• Result fusion using Reciprocal Rank Fusion (RRF)

Collection

Search is always performed against notes-hybrid.

How to search effectively

1. Construct the query

Use a natural language description of what you are trying to do.

Examples:

• restart a stuck kubernetes deployment
• internal api endpoint for resetting user passwords
• terraform s3 lifecycle drift issues

This query is used for:

• Dense embedding generation
• Sparse keyword extraction

2. Apply filters when appropriate

Use filters to narrow results when the domain is known.

Common filters:

• type = cli
• tool = kubectl / aws / terraform
• language = bash
• source = repo:infra

Example:

{
  "must": [
    { "key": "type", "match": { "value": "cli" } },
    { "key": "tool", "match": { "value": "kubectl" } }
  ]
}

3. Interpret results carefully

• Prefer notes with clear context
• Prefer newer notes if multiple exist
• Refine and re-run search if results are close but incomplete

Tool usage

Use the qdrant-search-notes MCP tool with:

• Query text
• Optional payload filters
• Result limit (typically 5–10)

The tool:

• Executes dense and sparse searches
• Fuses results using RRF
• Returns ranked, agent-readable notes

Agent reminder

Before inventing a solution, check memory first.

If no relevant note exists and you learn something new:

1. Complete the task
2. Immediately use add-note to store the new knowledge