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Skillshub apify-actorization

Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.

install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/apify/agent-skills/apify-actorization" ~/.claude/skills/comeonoliver-skillshub-apify-actorization && rm -rf "$T"
manifest: skills/apify/agent-skills/apify-actorization/SKILL.md
source content

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.

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:

curl -fsSL https://apify.com/install-cli.sh | bash

# Or (Mac): brew install apify-cli
# Or (Windows): irm https://apify.com/install-cli.ps1 | iex
# Or: npm install -g apify-cli

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, then:

apify login -t $APIFY_TOKEN

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:

Quick Reference

LanguageInstallWrap Code
JS/TS
npm install apify
await Actor.init()
... 
await Actor.exit()
Python
pip install apify
async with Actor:
OtherUse 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

Important: Always use 

apify run
, not 
npm start
or 
python main.py
. The CLI sets up the proper environment and storage.

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: Rental (monthly subscription) or Free (open source).

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