apify-actorization

Apify Actorization

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.

Before initialization/install/deploy, inspect existing files and preserve their state. Confirm target account/Actor, source license, uploaded files/secrets, network targets and spending/charging limits. Authorizing local conversion does not authorize cloud upload, Store publication or monetization. Pin reviewed SDK/CLI/base images and verify schemas against that version.

Quick Start

1. Run apify init in project root
2. Wrap code with SDK lifecycle (see language-specific section below)
3. Configure .actor/input_schema.json
4. Test with apify run --input '{"key": "value"}'
5. Deploy with apify push

When to Use This Skill

• Converting an existing project to run on Apify platform
• Adding Apify SDK integration to a project
• Wrapping a CLI tool or script as an Actor
• Migrating a Crawlee project to Apify

Prerequisites

Verify apify CLI is installed:

apify --help

If not installed:

brew install apify-cli

# Or: npm install -g apify-cli
# Or install from an official release package that your OS package manager verifies

Verify CLI is logged in:

apify info  # Should return your username

If not logged in, check if APIFY_TOKEN environment variable is defined. If not, ask the user to generate one at https://console.apify.com/settings/integrations, add it to their shell or secret manager without putting the literal token in command history, then run:

apify login

Actorization Checklist

Copy this checklist to track progress:

• Step 1: Analyze project (language, entry point, inputs, outputs)
• Step 2: Run apify init to create Actor structure
• Step 3: Apply language-specific SDK integration
• Step 4: Configure .actor/input_schema.json
• Step 5: Configure .actor/output_schema.json (if applicable)
• Step 6: Update .actor/actor.json metadata
• Step 7: Test locally with apify run
• Step 8: Deploy with apify push

Step 1: Analyze the Project

Before making changes, understand the project:

1. Identify the language - JavaScript/TypeScript, Python, or other
2. Find the entry point - The main file that starts execution
3. Identify inputs - Command-line arguments, environment variables, config files
4. Identify outputs - Files, console output, API responses
5. Check for state - Does it need to persist data between runs?

Step 2: Initialize Actor Structure

Run in the project root:

apify init

This creates:

• .actor/actor.json - Actor configuration and metadata
• .actor/input_schema.json - Input definition for the Apify Console
• Dockerfile (if not present) - Container image definition

Step 3: Apply Language-Specific Changes

Choose based on your project's language:

• JavaScript/TypeScript: See js-ts-actorization.md
• Python: See python-actorization.md
• Other Languages (CLI-based): See cli-actorization.md

Quick Reference

Language	Install	Wrap Code
JS/TS	npm install apify	await Actor.init() ... await Actor.exit()
Python	pip install apify	async with Actor:
Other	Use CLI in wrapper script	apify actor:get-input / apify actor:push-data

Steps 4-6: Configure Schemas

See schemas-and-output.md for detailed configuration of:

• Input schema (.actor/input_schema.json)
• Output schema (.actor/output_schema.json)
• Actor configuration (.actor/actor.json)
• State management (request queues, key-value stores)

Validate schemas against @apify/json_schemas npm package.

Step 7: Test Locally

Run the actor with inline input (for JS/TS and Python actors):

apify run --input '{"startUrl": "https://example.com", "maxItems": 10}'

Or use an input file:

apify run --input-file ./test-input.json

Use the documented local CLI flow for the selected language; inspect storage purge defaults and preserve unrelated local data. Direct SDK/test execution may also be appropriate. Local execution can still make network requests or use cloud storage when configured; use synthetic fixtures and a test account.

Step 8: Deploy

apify push

This uploads and builds your actor on the Apify platform.

Monetization (Optional)

After deploying, you can monetize your actor in the Apify Store. The recommended model is Pay Per Event (PPE):

• Per result/item scraped
• Per page processed
• Per API call made

Configure PPE in the Apify Console under Actor > Monetization. Charge for events in your code with await Actor.charge('result').

Other options: other currently supported Store models or free execution. A free Actor is not automatically open-source; license and source availability are separate.

Pre-Deployment Checklist

• .actor/actor.json exists with correct name and description
• .actor/actor.json validates against @apify/json_schemas (actor.schema.json)
• .actor/input_schema.json defines all required inputs
• .actor/input_schema.json validates against @apify/json_schemas (input.schema.json)
• .actor/output_schema.json defines output structure (if applicable)
• .actor/output_schema.json validates against @apify/json_schemas (output.schema.json)
• Dockerfile is present and builds successfully
• Actor.init() / Actor.exit() wraps main code (JS/TS)
• async with Actor: wraps main code (Python)
• Inputs are read via Actor.getInput() / Actor.get_input()
• Outputs use Actor.pushData() or key-value store
• apify run executes successfully with test input
• generatedBy is set in actor.json meta section

Apify MCP Tools

If MCP server is configured, use these tools for documentation:

• search-apify-docs - Search documentation
• fetch-apify-docs - Get full doc pages

Otherwise, the MCP Server url: https://mcp.apify.com/?tools=docs.

Resources

• Actorization Academy - Comprehensive guide
• Apify SDK for JavaScript - Full SDK reference
• Apify SDK for Python - Full SDK reference
• Apify CLI Reference - CLI commands
• Actor Specification - Complete specification

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.