* feat: add 12 official Apify skills for web scraping and data extraction Add the complete Apify agent-skills collection as official vendor skills, bringing the total skill count from 954 to 966. New skills: - apify-actor-development: Develop, debug, and deploy Apify Actors - apify-actorization: Convert existing projects into Apify Actors - apify-audience-analysis: Audience demographics across social platforms - apify-brand-reputation-monitoring: Track reviews, ratings, and sentiment - apify-competitor-intelligence: Analyze competitor strategies and pricing - apify-content-analytics: Track engagement metrics and campaign ROI - apify-ecommerce: E-commerce data scraping for pricing intelligence - apify-influencer-discovery: Find and evaluate influencers - apify-lead-generation: B2B/B2C lead generation from multiple platforms - apify-market-research: Market conditions and geographic opportunities - apify-trend-analysis: Discover emerging trends across platforms - apify-ultimate-scraper: Universal AI-powered web scraper Existing skill fixes: - design-orchestration: Add missing description, fix markdown list spacing - multi-agent-brainstorming: Add missing description, fix markdown list spacing Registry and documentation updates: - Update skill count to 966+ across README.md, README.vi.md - Add Apify to official sources in SOURCES.md and all README variants - Register new skills in catalog.json, skills_index.json, bundles.json, aliases.json - Update CATALOG.md category counts (data-ai: 152, infrastructure: 95) Validation script improvements: - Raise description length limit from 200 to 1024 characters - Add empty description validation check - Apply PEP 8 formatting (line length, spacing, trailing whitespace) * refactor: truncate skill descriptions in SKILL.md files and revert description length validation to 200 characters. * feat: Add `apify-ultimate-scraper` to data-ai and move `apify-lead-generation` from business to general categories.
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name, description
| name | description |
|---|---|
| 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). Us... |
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 initin 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:
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 initto 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.jsonmetadata - Step 7: Test locally with
apify run - Step 8: 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 ConsoleDockerfile(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
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.jsonexists with correct name and description.actor/actor.jsonvalidates against@apify/json_schemas(actor.schema.json).actor/input_schema.jsondefines all required inputs.actor/input_schema.jsonvalidates against@apify/json_schemas(input.schema.json).actor/output_schema.jsondefines output structure (if applicable).actor/output_schema.jsonvalidates against@apify/json_schemas(output.schema.json)Dockerfileis present and builds successfullyActor.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 runexecutes successfully with test inputgeneratedByis set in actor.json meta section
Apify MCP Tools
If MCP server is configured, use these tools for documentation:
search-apify-docs- Search documentationfetch-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