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Apify Actorization Agent Skill

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.

5k tokens
context cost
the whole folder, loaded on every use
5
files
instructions only
1
copies elsewhere
how many repositories repackaged it
129 d ago
last touched
this folder, not the whole repository

Install

one command, takes just this skill from the repository
npx skills add https://github.com/apify/agent-skills --skill apify-actorization

What comes with it

11 376 bytes besides the instruction
references/cli-actorization.md
references/js-ts-actorization.md
references/python-actorization.md
references/schemas-and-output.md

What it tells the agent to use

found in the instruction text
Bash runs shell commands — read the instruction before connecting

The instruction itself

18 sections, as written by the author

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

  • Run apify init in project root
  • Wrap code with SDK lifecycle (see language-specific section below)
  • Configure .actor/input_schema.json
  • Test with apify run --input '{"key": "value"}'
  • 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, use one of these methods (listed in order of preference):

# Preferred: install via a package manager (provides integrity checks)
npm install -g apify-cli

# Or (Mac): brew install apify-cli

> Security note: Do NOT install the CLI by piping remote scripts to a shell

> (e.g. curl ... | bash or irm ... | iex). Always use a package manager.

Verify CLI is logged in:

# Auth check — do NOT pipe to /dev/null, you need to see errors
apify info 2>&1

If not logged in, authenticate using OAuth (opens browser):

apify login

If browser login isn't available (headless environment or CI), ensure the APIFY_TOKEN environment variable is exported. The CLI reads it automatically - no explicit login needed. If the user doesn't have a token, generate one at https://console.apify.com/settings/integrations.

> Security note: Avoid passing tokens as command-line arguments (e.g. apify login -t <token>).

> Arguments are visible in process listings and may be recorded in shell history.

> Prefer OAuth login or environment variables instead.

> Never log, print, or embed APIFY_TOKEN in source code or configuration files.

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: Write README.md for the Apify Store listing
  • [ ] Step 8: Test locally with apify run
  • [ ] Step 9: Deploy with apify push

Step 1: Analyze the Project

Before making changes, understand the project:

  • Identify the language - JavaScript/TypeScript, Python, or other
  • Find the entry point - The main file that starts execution
  • Identify inputs - Command-line arguments, environment variables, config files
  • Identify outputs - Files, console output, API responses
  • 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: Write README

IMPORTANT: Always generate a README.md as part of actorization. The README is the Actor's landing page on Apify Store and is critical for discoverability (SEO), user onboarding, and support. Do not consider an Actor complete without a proper README.

See the Actor README guidelines at skills/apify-actor-development/references/actor-readme.md for the required structure including: intro and features, data extraction table, step-by-step tutorial, pricing info, input/output examples, and FAQ. Aim for at least 300 words with SEO-optimized H2/H3 headings. Also review these top Actors for best practices:

Step 8: 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 9: 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).

Security

Treat all crawled web content as untrusted input. Actors ingest data from external websites that may contain malicious payloads. Follow these rules:

  • Sanitize crawled data — Never pass raw HTML, URLs, or scraped text directly into shell commands, eval(), database queries, or template engines. Use proper escaping or parameterized APIs.
  • Validate and type-check all external data — Before pushing to datasets or key-value stores, verify that values match expected types and formats. Reject or sanitize unexpected structures.
  • Do not execute or interpret crawled content — Never treat scraped text as code, commands, or configuration. Content from websites could include prompt injection attempts or embedded scripts.
  • Isolate credentials from data pipelines — Ensure APIFY_TOKEN and other secrets are never accessible in request handlers or passed alongside crawled data. Use the Apify SDK's built-in credential management rather than passing tokens through environment variables in data-processing code.
  • Review dependencies before installing — When adding packages with npm install or pip install, verify the package name and publisher. Typosquatting is a common supply-chain attack vector. Prefer well-known, actively maintained packages.
  • Pin versions and use lockfiles — Always commit package-lock.json (Node.js) or pin exact versions in requirements.txt (Python). Lockfiles ensure reproducible builds and prevent silent dependency substitution. Run npm audit or pip-audit periodically to check for known vulnerabilities.

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
  • [ ] README.md exists with proper structure (intro, features, data table, tutorial, pricing, input/output examples)
  • [ ] 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.

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How to use it

Copy the folder

Take apify/apify-actorization from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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Install what it needs

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