Catch schema violations before Apify does
Run your actor with test input and compare every output field against its declared dataset schema. Type mismatches, missing fields, undeclared fields, and null handling issues — all caught in one run with a 0-100 compliance score.
Maps declared schema types (string, integer, number, boolean, array, object) to JavaScript runtime types and flags every mismatch with the exact field path.
Lists every output field not defined in the dataset schema. These fields won't appear in the Store's table view and may indicate data leaks.
Checks every schema-declared field exists in at least one output item. Missing fields indicate broken extractors or changed data sources.
Identifies fields with null values where the schema doesn't declare nullable: true — a common source of downstream pipeline errors.
Flags fields with mixed types across items (e.g., rating is sometimes a string, sometimes a number) regardless of schema declarations.
Weighted scoring: errors (-10 points), warnings (-3), undeclared fields (-2), type inconsistencies (-5). Score of 90+ means minor issues only.
{
"actorName": "ryanclinton/website-contact-scraper",
"schemaFound": true,
"schemaFields": 12,
"outputFields": 15,
"totalItems": 3,
"mismatches": [
{ "path": "price", "expected": "number", "actual": "string", "severity": "error" },
{ "path": "email", "expected": "non-null", "actual": "null values found", "severity": "warning" }
],
"undeclaredFields": ["_debug", "scrapedAt", "rawHtml"],
"missingRequired": ["phoneNumber"],
"score": 72,
"passed": false
}Connect your Apify token and enter the actor ID
The tool runs the actor on your account and analyzes the output
Get a detailed report with actionable fixes — results cached for free