1. Export Overview
Forge exports structured vault data for dashboards, audits, AI workflows, reporting, and long-term reference.
Exports help answer questions like:
- What kinds of notes exist in this vault?
- Which areas are growing?
- Which metadata values are most common?
- What relationships exist between notes?
- Which notes are stale or inconsistent?
- What should external tools know about this vault?
Forge exports are designed to stay readable inside Obsidian while also being useful to external tooling.
Export Commands
Forge includes two export commands:
| Command | Purpose |
|---|---|
Forge: Export Vault Overview | Generate overall vault summaries and inventory exports |
Forge: Export Ontology Index | Generate relationship indexes from note structures |
Export Vault Overview
This command generates three files:
| File | Purpose |
|---|---|
vault-inventory.json | Machine-readable note inventory |
vault-meta.json | Aggregate vault statistics |
vault-export.md | Human-readable export summary |
Exports are written to:
A-I/Forge/Exports
Generated Files
vault-inventory.json
A flat inventory of notes in the vault.
Each item may include:
- path
- filename
- type
- status
- tags
- domain
- metadata fields
Useful for:
- external scripts
- AI workflows
- vault analysis
- reporting
- dashboards
vault-meta.json
Aggregate vault statistics.
Examples:
- notes by type
- notes by status
- notes by domain
- export timestamps
- schema version metadata
Useful for:
- audits
- dashboards
- trend tracking
- vault snapshots
vault-export.md
A readable Obsidian note summarizing the export.
Includes:
- vault totals
- grouped summaries
- metadata counts
- Dataview-friendly fields
- relationship summaries
This note is designed for humans first.
Why Exports Matter
As vaults grow, it becomes harder to understand:
- what exists
- what is missing
- what is outdated
- how notes relate
- where inconsistencies appear
Exports help surface those patterns.
That becomes especially useful for:
- Dataview dashboards
- Bases
- AI-assisted workflows
- large research vaults
- long-lived project systems
- shared vaults
Dataview and Bases
Consistent metadata makes exports dramatically more useful.
Forge exports work best when:
- note types are predictable
- statuses are standardized
- tags are normalized
- schemas are enforced consistently
This is why schema validation and linting matter.
Reliable metadata produces reliable exports.
Reliable exports produce better dashboards, queries, Bases, and automation workflows.
Dashboard Generation
Forge can generate a dashboard note alongside exports.
The dashboard is created once and never overwritten automatically.
You are free to customize it afterward.
Typical dashboards include:
- note counts
- stale notes
- notes by type
- notes by status
- relationship indexes
- Dataview summaries
Export Workflow Example
A common workflow looks like this:
- Run Vault Lint
- Normalize metadata
- Repair inconsistencies
- Re-run lint
- Export vault overview
- Review dashboards and summaries
This creates a feedback loop where the vault becomes easier to maintain over time.
AI Workflow Usage
Exports are intentionally AI-friendly.
Many users export vault summaries for:
- AI context windows
- assistant memory systems
- semantic indexing
- retrieval workflows
- external search pipelines
- reporting systems
Forge does not send vault data anywhere automatically.
Exports remain local files inside your vault unless you choose to use them elsewhere.
Privacy Considerations
Forge exports stay inside your vault by default.
If you use exports with external tools or AI systems:
- review exported content first
- avoid exporting sensitive vault sections
- use private fields or exclusions where appropriate
- consider separate vaults for sensitive material
Export Folder Structure
Typical export structure:
A-I/Forge/Exports/
├── vault-export.md
├── vault-inventory.json
├── vault-meta.json
└── vault-dashboard.md
Relationship indexes generate additional files.
Those are covered in:
