vault-indexer

Index Obsidian vault metadata into a SQLite database for structured note retrieval.

1|1|Updated Feb 8, 2026

Search Tags:#markdown #knowledge management #sqlite #obsidian #metadata search #vault indexing

Ready to run

npx skills add https://github.com/dapperdivers/roundtable-arsenal --skill vault-indexer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: vault-indexer
Source: https://github.com/dapperdivers/roundtable-arsenal/tree/main/shared/vault-indexer
Command: npx skills add https://github.com/dapperdivers/roundtable-arsenal --skill vault-indexer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires sqlite3, python3, yq, and includes scripts (resource) components.

What problem does it solve?

This Skill replaces slow grep-based searching across large Obsidian vaults with a fast SQLite metadata index, making it easier to locate notes by structure, tags, dates, paths, and other attributes.

Core Features & Use Cases

SQLite Vault Indexing: Scans Markdown files and builds a searchable database of note metadata, tags, links, titles, and timestamps.
Structured Note Queries: Supports filtering notes by tag, date range, path, type, frontmatter presence, and output format for research and knowledge management workflows.
Use Case: Search a large Obsidian vault for recent security briefings, tagged project notes, or unorganized documents without manually scanning thousands of files.

Quick Start

Use the vault-indexer skill to build an index of my Obsidian vault and find all notes tagged with security from the last 7 days.

Frequently Asked Questions about vault-indexer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I search Obsidian vault metadata faster than using grep?▼

Obsidian vault metadata search is accelerated by indexing Markdown files into a SQLite database, replacing slow grep operations with structured queries. This allows fast filtering by tags, dates, paths, and frontmatter attributes across large archives.

Can I filter Markdown notes by tag and date range in an Obsidian vault?▼

Yes, you can filter Markdown notes by tag and date range by querying the indexed SQLite database. The vault indexer extracts frontmatter, tags, and timestamps, enabling structured discovery for specific timeframes without manual file scanning.

Do I need sqlite3 and python3 to index Markdown frontmatter?▼

Yes, sqlite3, python3, and yq are required dependencies to parse Markdown frontmatter and build the searchable database index. These tools handle metadata extraction and maintain the structured note index for fast vault queries.

What is the best way to find unorganized documents in a large Obsidian vault?▼

The best way to find unorganized documents is using a SQLite vault index to query for notes lacking specific tags or frontmatter. This structured search approach instantly identifies files without metadata, streamlining vault maintenance tasks across thousands of notes.

Does vault indexing work for link analysis and knowledge management workflows?▼

Vault indexing works for link analysis and knowledge management by extracting note links and titles into the database. This supports structured queries to map note relationships and discover content within Markdown archives.

Why is my Obsidian vault search slow across thousands of Markdown files?▼

Obsidian vault search becomes slow when relying on text scanning across thousands of Markdown files. Indexing metadata into a SQLite database resolves this by enabling instant structured queries on tags, dates, and paths instead of manual scanning.