apify-actorization
Actorization converts existing software into reusable serverless applications compatible with the Apify platform.
Skill by sickn33
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About
Use cases: devops, cloud
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/apify-actorization
What's inside
- Skill name
apify-actorization- Description
- 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.
- License
- MIT
- Instructions
- 187 lines in SKILL.md · view on GitHub
Files (5)
- SKILL.md
- cli-actorization.md · references/
- js-ts-actorization.md · references/
- python-actorization.md · references/
- schemas-and-output.md · references/
SKILL.md (first lines)
# 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:
```bash
apify --help
```
If not installed:
```bash
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:
```bash
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:
```bash
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:
```bash
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](references/js-ts-actorization.md)
- **Python**: See [python-actorization.md](references/python-actorization.md)
- **Other Languages (CLI-based)**: See [cli-actorization.md](references/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](references/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):
```bash
apify run --input '{"startUrl": "https://example.com", "maxItems": 10}'
```From sickn33/agentic-awesome-skills, MIT.
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Signals
- Stars
- 48,428
- Forks
- 7,039
- Open issues
- 0
- Last commit (this folder)
- Oct 24, 2026 (7 days ago)
- Last release
- Oct 24, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Website
- aaskills.tech/
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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apify-actorization skill. Agent Mart. https://agentmart.dev/skills/sickn33-apify-actorization (last updated 2026-10-24)