/**
 * Incremental JSON Schema learning — type union over observed samples.
 *
 * Used by the Screen Designer to build `generatedOutputSchema` from real MCP tool
 * responses when the server doesn't ship a native `outputSchema`. Each captured
 * response is merged into the running schema via {@link mergeSchema}; the result
 * converges as more samples arrive.
 *
 * Algorithm:
 * - Object properties: union of keys. A property present in one sample but missing
 *   from another is marked optional (dropped from `required`).
 * - Array items: recursive merge across element schemas from all samples.
 * - Primitives of the same type: identity.
 * - `null` + any type: sets `nullable: true` on that type.
 * - Type conflicts (e.g. string + number): collapsed into `anyOf`.
 *
 * Pure — no I/O, no DB, no clock. Safe to call from Lambda, edge, or tests.
 */
import type { JsonSchema, JsonValue } from "../types/data-contract.js";
/** Infer a JSON Schema from a single JSON value. */
export declare function inferSchema(value: JsonValue): JsonSchema;
/**
 * Merge a new observed sample into an existing schema. If `existing` is null,
 * returns the schema inferred from `sample` alone.
 */
export declare function mergeSchema(existing: JsonSchema | null | undefined, sample: JsonValue): JsonSchema;
/**
 * Merge two schemas into one that accepts values satisfying either. Exported
 * for the seeder path (combining two known schemas without sampling).
 */
export declare function mergeTwoSchemas(a: JsonSchema, b: JsonSchema): JsonSchema;
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