What problem does it solve? Apify Actors need output schema files so the Apify Console knows how to display run results, but writing dataset_schema.json, output_schema.json, and key_value_store_schema.json by hand is error-prone and requires deep knowledge of Apify-specific JSON Schema conventions. ## Core Features & Use Cases - Source Code Analysis: Scans the Actor's code for pushData/setValue calls and existing TypeScript interfaces or Python type definitions to derive every output field. - Schema Generation: Produces dataset_schema.json with field definitions and display views, output_schema.json with result templates, and key_value_store_schema.json with collections when the Actor uses the key-value store. - Configuration Wiring: Updates actor.json to reference the generated schema files and migrates inline storage definitions. - Use Case: You built an Actor that scrapes product listings and pushes results to a dataset. Run this Skill to generate a complete dataset schema with anonymized examples, nullable fields, and an overview view, then validate it against the checklist before committing. ## Quick Start Analyze my Actor's source code and generate the dataset, output, and key-value store schema files, then update actor.json to reference them.
