Builder

The /builder page lets you visually build a table schema:

1. Paste JSON data (or upload a CSV) in the left panel
2. Click Generate Schema — the schema is auto-inferred from your data
3. A live table preview appears with filters, sorting, and row details
4. Edit the Schema JSON directly and click Apply for instant updates
5. Click Export TS to copy the generated createTableSchema(...) code

Type Inference

The inference engine detects column types from your data:

• ISO 8601 strings / Unix-ms numbers → timestamp + timerange filter
• Booleans → boolean + checkbox filter
• Numbers with varying values → number + slider filter
• Strings with ≤10 distinct values → enum + checkbox filter
• Arrays of strings → array with enum items
• Plain objects → record (not filterable)

Post-inference heuristics apply smart defaults (ID-like → code display, latency → "ms" unit, log level → defaultOpen, etc.).

Example Datasets

Example datasets (Pokemon, HTTP Logs, Space Missions, Cocktails, Orders, Issues, Movies, RPG Characters) are included to explore different configurations.

Serialization & AI

The schema serializes to a function-free JSON descriptor for AI agents, MCP tools, or remote storage.

// Schema → JSON
const json = tableSchema.toJSON();
// JSON.stringify(tableSchema) also works
 
// JSON → Schema (e.g. from an AI agent)
const reconstructed = createTableSchema.fromJSON(json);
 
// JSON → TypeScript code
import { schemaToTypeScript } from "@/lib/table-schema/to-typescript";
const tsCode = schemaToTypeScript(json);

Custom renderers (display("custom", ...), filter.component, sheet.component) are functions and cannot be serialized. They are stripped during toJSON() and must be applied manually on reconstructed schemas.