发现优质的 AI Agent 技能

Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.

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The Actor output schema builds upon the schemas for the dataset and key-value store. It specifies where an Actor stores its output and defines templates for accessing that output. Apify Console uses these output definitions to display run results.

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The key-value store schema organizes keys into logical groups called collections for easier data management.

The input schema defines the input parameters for an Actor. It's a JSON object comprising various field types supported by the Apify platform.

The dataset schema defines how your Actor's output data is structured, transformed, and displayed in the Output tab in the Apify Console.

The `.actor/actor.json` file contains the Actor's configuration including metadata, schema references, and platform settings.

**Important:** Before you begin, fill in the `generatedBy` property in the meta section of `.actor/actor.json`. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.

This file contains detailed patterns, checklists, and code samples referenced by the skill.

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> Plan for API evolution from day one.