sem-search-a

Included with Lifetime

$97 forever

This skill should be used when the user asks to "search notes", "find similar notes", "semantic search", "reindex vault", "rebuild index", "query vault", or needs to find notes by meaning rather than keywords.

General

What this skill does


> **Action skill** — Semantic search operations: BM25, vector search, hybrid search, reindexing.

# Semantic Search — qmd

Search the vault by meaning using **qmd**, a local semantic search engine for markdown. BM25 + vector search + LLM re-ranking, all local. No cloud APIs.

## Setup (One-Time)

If qmd is not installed:

```bash
brew install oven-sh/bun/bun        # Bun runtime (if not installed)
bun install -g github:tobi/qmd      # qmd itself
```

Register the vault as a collection:

```bash
qmd collection add "<vault-path>" --name vault
```

Build initial embeddings (~2GB models downloaded on first run):

```bash
qmd embed
```

Index stored at `~/.cache/qmd/index.sqlite` — outside vault, no gitignore needed.

## Commands

### Reindex

When invoked with `--reindex` or after batch changes to the vault:

```bash
qmd update    # Re-index all collections (picks up new/changed/deleted files)
qmd embed     # Rebuild vector embeddings (needed after first install or model change)
```

Use `qmd update` for routine reindexing. Use `qmd embed` only for initial setup or embedding model changes.

### Quick Search (BM25)

Fast keyword search. Good for finding notes that mention specific terms.

```bash
qmd search "prediction market pricing"
```

### Semantic Search (Vector)

Vector similarity search. Finds conceptually related content even without keyword overlap.

```bash
qmd vsearch "how do agents maintain context across sessions"
```

This is the most useful search mode for finding related notes, confirming filing destinations, and discovering connections.

### Best Quality (Hybrid + LLM Re-ranking)

Combines BM25 + vector search + LLM re-ranking with 6 parallel searches. Highest quality but slower.

```bash
qmd query "what patterns emerge in agentic development workflows"
```

Use for thorough exploration. Overkill for quick lookups.

### Get Document

Retrieve the content of a specific document by path:

```bash
qmd get "2-Areas/ai-dev-ecosystem/2025-01-21_agentic-learnings.md"
```

### Output Formats

Append format flags for programmatic use:

- `--json` — JSON output (for parsing results)
- `--csv` — CSV output
- `--md` — Markdown formatted
- `--files` — File paths only (one per line, useful for piping)

Example: `qmd vsearch "agentic development" --files` returns just paths.

## When to Use Which

| Need | Command | Speed |
|------|---------|-------|
| Find notes mentioning a term | `qmd search` | Fast |
| Find conceptually similar notes | `qmd vsearch` | Medium |
| Thorough exploration of a topic | `qmd query` | Slower |
| Confirm filing destination | `qmd vsearch` | Medium |
| Discover cross-area connections | `qmd query` | Slower |

## Integration with Other Skills

- **auto-process-a**: Uses `qmd vsearch` to confirm filing destinations
- **backlinks-a**: Uses `qmd vsearch` or `qmd query` to find semantically similar notes
- **find-connections-a**: Uses `qmd query` for thorough connection discovery
- **librarian agent**: Runs `qmd update` after batch processing

## Troubleshooting

- **"No collections"**: Run `qmd collection add "<vault-path>" --name vault`
- **"No embeddings"**: Run `qmd embed` (first time takes a few minutes)
- **Stale results**: Run `qmd update` to re-index
- **Check collections**: `qmd collection list` shows registered collections

Files: 1

Size: 3.6 KB

Complexity: 12/100

Category: General

Source: https://github.com/jsai23/claude-tooling/tree/main/plugins/vault/skills/sem-search-a

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