About this skill
The `/q` skill offers rapid and powerful search capabilities for personal knowledge vaults built upon SQLite with an FTS5 index. Designed to integrate directly into an AI agent's workflow, it allows users to quickly retrieve information from large collections of notes, such as architectural documentation, project notes, or personal knowledge bases. This skill supports a wide array of search patterns, including full-text queries for specific words or phrases, filtering by note type (e.g., ADRs, Projects, Tasks), and searching by specific tags (e.g., `tag:technology/aws`). Additionally, it provides specialized queries for identifying recently modified notes, finding all backlinks to a specific note, or discovering 'orphan' notes that have no inbound links, aiding in knowledge graph maintenance and discovery. By executing optimized SQLite queries, the `/q` skill dramatically reduces search times from seconds to milliseconds, making information retrieval highly efficient. It's an essential tool for anyone managing a structured knowledge base who needs quick, precise access to their stored information directly through their AI agent.
Best use case
This skill is primarily for knowledge workers, developers, architects, or anyone managing a large, structured personal knowledge vault (e.g., a Zettelkasten or project documentation) who needs to quickly find, analyze, and retrieve specific information. It's ideal for scenarios where rapid access to organized data, contextual retrieval of linked information, or identification of knowledge gaps is critical for productivity and decision-making.
Fast SQLite-based vault search using FTS5 full-text search index
Users should expect a markdown-formatted table of relevant note paths, titles, and snippets, retrieved rapidly from their SQLite vault.
Practical example
Example input
/q architecture patterns
Example output
| path | match | | :------------------------- | :-------------------------------------------------------------------------------- | | docs/patterns/design.md | Design →patterns← are common solutions to recurring software design problems... | | docs/architecture/types.md | Explores various architectural →patterns← like microservices, monoliths, etc. |
When to use this skill
- When you need to quickly find information in a large SQLite-backed knowledge vault.
- When performing full-text searches, filtering by note type, or searching by specific tags.
- When exploring connections between notes (backlinks) or finding unlinked notes (orphans).
- When you need to retrieve recently modified notes for review or context.
When not to use this skill
- If you do not have a SQLite-based knowledge vault, specifically one built with `npm run vault:index`.
- For searching external websites, general web searches, or databases not configured as this vault.
- If you require complex analytical queries or data transformations beyond simple search and filtering.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/q/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How q Compares
| Feature / Agent | q | Standard Approach |
|---|---|---|
| Platform Support | Claude | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | medium | N/A |
Frequently Asked Questions
What does this skill do?
Fast SQLite-based vault search using FTS5 full-text search index
Which AI agents support this skill?
This skill is designed for Claude.
How difficult is it to install?
The installation complexity is rated as medium. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# /q - Quick SQLite Search
Fast vault search using the SQLite FTS5 index. Returns results in milliseconds instead of seconds.
## Prerequisites
The SQLite index must be built first:
```bash
npm run vault:index
```
## Usage Patterns
### Full-text Search
```bash
/q architecture patterns
/q "event driven" # Phrase search
/q kafka integration # Multiple terms (AND)
```
### Type Filter
```bash
/q type:Adr # All ADRs
/q type:Project status:active
/q type:Task priority:high
```
### Tag Search
```bash
/q tag:technology/aws
/q tag:project/your-project
```
### Recent Notes
```bash
/q recent # Modified in last 7 days
/q recent:30 # Modified in last 30 days
```
### Backlinks
```bash
/q backlinks:"Project - Your Project"
/q backlinks:"System - Your System"
```
### Orphans
```bash
/q orphans # Notes with no backlinks
```
## Implementation
Execute the appropriate SQLite query based on the search pattern.
### Full-text Search Query
```bash
sqlite3 .data/vault.db -markdown "
SELECT n.path, snippet(fts_content,1,'→','←','...',40) as match
FROM fts_content
JOIN notes n ON fts_content.rowid = n.id
WHERE fts_content MATCH '<search_terms>'
ORDER BY rank
LIMIT 20
"
```
### Type Filter Query
```bash
sqlite3 .data/vault.db -markdown "
SELECT path, title, status, priority
FROM notes
WHERE type = '<Type>'
ORDER BY modified DESC
LIMIT 20
"
```
### Tag Search Query
```bash
sqlite3 .data/vault.db -markdown "
SELECT n.path, n.title, n.type
FROM notes n
JOIN tags t ON n.id = t.note_id
WHERE t.tag = '<tag>'
ORDER BY n.modified DESC
LIMIT 20
"
```
### Recent Notes Query
```bash
sqlite3 .data/vault.db -markdown "
SELECT path, title, type, modified
FROM notes
WHERE modified >= date('now', '-<days> days')
ORDER BY modified DESC
LIMIT 30
"
```
### Backlinks Query
```bash
sqlite3 .data/vault.db -markdown "
SELECT n.path, n.title, n.type
FROM notes n
JOIN links l ON n.id = l.source_id
WHERE l.target_path LIKE '%<note_name>%'
ORDER BY n.modified DESC
"
```
### Orphans Query
```bash
sqlite3 .data/vault.db -markdown "
SELECT n.path, n.title, n.type
FROM notes n
LEFT JOIN links l ON n.id = l.target_id
WHERE l.target_id IS NULL
AND n.type NOT IN ('DailyNote', 'MOC', 'Dashboard', 'Query')
ORDER BY n.modified DESC
"
```
## Performance
| Query Type | Grep/Glob | SQLite | Improvement |
| ----------- | --------- | ------ | ----------- |
| Full-text | 5-15 sec | 0.01s | ~1000x |
| Type filter | 3-5 sec | 0.007s | ~500x |
| Tag search | 2-5 sec | 0.007s | ~500x |
| Backlinks | 10+ sec | 0.01s | ~1000x |
## Rebuilding the Index
The index should be rebuilt when vault content changes significantly:
```bash
npm run vault:index # Full rebuild
npm run vault:stats # View current statistics
```
## Tips
1. **Combine filters**: `/q type:Adr status:proposed technology/aws`
2. **Use phrases**: `/q "data platform"` for exact matches
3. **Wildcards**: SQLite FTS5 supports `*` wildcards: `/q architect*`
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