vaultage-search
Skill2 starsChanged 10 months agoMITView on GitHub
Search the Obsidian vault using semantic embeddings or SQL queries on frontmatter. Set your vault path via environment variable: Options: - --query: Search query text - --n-results: Number of results (default 10) - --folder: Filter to specific folder - --where: JSON filter for metadata Available columns: path, folder, filename, title, status, priority, due, tags, created, modified The search scripts require: - Python 3.10+ - sqlite-vec or chromadb for embeddings - sentence-transformers for embedding generation Install dependencies:
- Installs packages
In this repository17 other files it gives its agents.
- react-best-practices/AGENTS.mdAGENTS.md
- agent-browserSkill
- claudeceptionSkill
- devlog-harvesterSkill
- humanizerSkill
- knowledge-forgeSkill
- loop-maestroSkill
- notebooklmSkill
- obsidian-bridgeSkill
- portfolio-forgeSkill
- project-analyzerSkill
- pr-review-resolverSkill
- vercel-react-best-practicesSkill
- vaultage-captureSkill
- vaultage-dailySkill
- vaultage-inboxSkill
- web-design-guidelinesSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 3
Search the Obsidian vault using semantic embeddings or SQL queries on frontmatter.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Vaultage Search Skill
Search the Obsidian vault using semantic embeddings or SQL queries on frontmatter.
Configuration
Set your vault path via environment variable:
export VAULTAGE_PATH="$HOME/Documents/Vaultage" # Customize to your vault locationTrigger Phrases
- "search vault for"
- "find in vaultage"
- "query vault notes"
- "semantic search"
Usage
Semantic Search (embeddings-based)
python "$VAULTAGE_PATH/.claude/skills/vault-search/scripts/search.py" --query "your search query" --n-results 10Options:
--query: Search query text--n-results: Number of results (default 10)--folder: Filter to specific folder--where: JSON filter for metadata
SQL Query (frontmatter database)
python "$VAULTAGE_PATH/.claude/skills/vault-search/scripts/dataview.py" "SELECT path, title FROM notes WHERE status = 'active' ORDER BY modified DESC LIMIT 20"Available columns: path, folder, filename, title, status, priority, due, tags, created, modified
Rebuild Index
python "$VAULTAGE_PATH/.claude/skills/vault-search/scripts/index.py"Setup
The search scripts require:
- Python 3.10+
- sqlite-vec or chromadb for embeddings
- sentence-transformers for embedding generation
Install dependencies:
pip install chromadb sentence-transformers pyyamlPARA Structure
- 00_Inbox: Unprocessed items
- 01_Projects: Active projects with deadlines
- 02_Areas: Ongoing responsibilities
- 03_Resources: Reference materials
- 04_Archive: Completed/inactive items
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