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v2026.05.11
Visualize how fields depend on each other in your Airtable base.
Analyze table-to-table relationships and dependencies in your base structure.
Visualize formula logic as interactive flowcharts. IF statements become decision diamonds, AND/OR become logic gates, and field references can be expanded to show their formulas.
Depth for expanding field references
Optimize and compress complex Airtable formulas by replacing field references with their formulas.
How many levels deep to compress. Leave empty for full compression.
Format for field references in output.
How to format the displayed formula.
Generate a CSV report of all formula fields in the selected table with compressed versions.
Identify and analyze the most complex computed fields in your base. Higher scores indicate more dependencies and cross-table relationships.
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| Score ↕ | Table ↕ | Field ↕ | Type | Depth ↕ | ← Deps ↕ | → Deps ↕ | X-Table ↕ |
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| Click "Refresh Scorecard" to analyze your base | |||||||
Find fields with zero inbound references — not used in any formula, rollup, lookup, or count. These may be candidates for cleanup.
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| Table ↕ | Field ↕ | Type ↕ | Outbound Refs ↕ | Status |
|---|---|---|---|---|
| Click "Scan for Unused Fields" to analyze your base | ||||
An unused field has zero inbound references — no other field in your base uses it in a formula, rollup, lookup, or count. These fields may still contain valuable data but aren't being computed or displayed elsewhere. Consider reviewing them to determine if they can be removed or consolidated.
Test formulas by entering values for dependent fields and seeing the computed result.
Format for field references in formulas.
Generate PostgreSQL CREATE TABLE statements from your Airtable schema.
How to name PostgreSQL columns.
Which Airtable field types to include.
Attempts to convert Airtable formulas to PostgreSQL syntax. Limited support.
Generate production-ready code from your Airtable schema. Choose your workflow and get tailored code packages for your use case.
Generate efficient Python evaluators for computed fields (formulas, lookups, rollups). These evaluators only recalculate fields when their dependencies change, enabling incremental updates.
Choose the table to generate an evaluator for.
Choose how fields are accessed in generated code.
View a summary matrix of field types across all tables in your base.
Note: This tab has been renamed to "Code Generator" with an improved workflow-based interface. This legacy version is kept for backward compatibility.
Generate TypeScript, Python, or SQL code from your Airtable schema. Create type definitions, SQL schemas with computed fields (formulas, lookups, rollups), and views for easy querying.
Choose the target language for type generation.
Choose the SQL database dialect.
Include helper type definitions for Airtable-specific types.
Generate SQL functions/triggers for Airtable computed fields.
Create SQL views for easy querying with all computed fields.
To use this tool with your own Airtable bases, you'll need to create a Personal Access Token (PAT).
data.records:readschema.bases:read
You'll also need your Base ID, which you can find in your base's URL: airtable.com/appXXXXXXXXXXXXX/...
Note: Your API key is stored only in your browser's local storage and is never sent to any server except Airtable's API.
No problem! You can try out the tool with our sample data to see how it works.
Upload a JSON file matching the sample schema format (must include a top-level tables array).