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Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.","LongLeo287\u002FOmniClaw","LongLeo287","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F141803367?v=4","01M6JK75C62VCNZKR5BRZ386YV","LongLeo","01M6JK75GQ78TSP1ZPXNKK3MCH",9,"MIT","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fskills\u002Fagent_skills\u002Fskills\u002Fapify_actorization\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"apify","apify actorization","use","Existing","manager","as","context manager","exit","async","Wrapper","cli","context","convert","projects","Tools","code","init","javascript","python","typescript","2026-11-10 10:12:30",false,"---\nname: apify-actorization\ndescription: Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript\u002FTypeScript (SDK with Actor.init\u002Fexit), 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.\n---\n\n# Apify Actorization\n\nActorization 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.\n\n## Quick Start\n\n1. Run `apify init` in project root\n2. Wrap code with SDK lifecycle (see language-specific section below)\n3. Configure `.actor\u002Finput_schema.json`\n4. Test with `apify run --input '{\"key\": \"value\"}'`\n5. Deploy with `apify push`\n\n## When to Use This Skill\n\n- Converting an existing project to run on Apify platform\n- Adding Apify SDK integration to a project\n- Wrapping a CLI tool or script as an Actor\n- Migrating a Crawlee project to Apify\n\n## Prerequisites\n\nVerify `apify` CLI is installed:\n\n```bash\napify --help\n```\n\nIf not installed, use one of these methods (listed in order of preference):\n\n```bash\n# Preferred: install via a package manager (provides integrity checks)\nnpm install -g apify-cli\n\n# Or (Mac): brew install apify-cli\n```\n\n> **Security note:** Do NOT install the CLI by piping remote scripts to a shell\n> (e.g. `curl … | bash` or `irm … | iex`). Always use a package manager.\n\nVerify CLI is logged in:\n\n```bash\napify info  # Should return your username\n```\n\nIf not logged in, check if the `APIFY_TOKEN` environment variable is defined (if not, ask the user to generate one at https:\u002F\u002Fconsole.apify.com\u002Fsettings\u002Fintegrations and then define `APIFY_TOKEN` with it).\n\nThen authenticate using one of these methods:\n\n```bash\n# Option 1 (preferred): The CLI automatically reads APIFY_TOKEN from the environment.\n# Just ensure the env var is exported and run any apify command — no explicit login needed.\n\n# Option 2: Interactive login (prompts for token without exposing it in shell history)\napify login\n```\n\n> **Security note:** Avoid passing tokens as command-line arguments (e.g. `apify login -t \u003Ctoken>`).\n> Arguments are visible in process listings and may be recorded in shell history.\n> Prefer environment variables or interactive login instead.\n> Never log, print, or embed `APIFY_TOKEN` in source code or configuration files.\n> Use a token with the minimum required permissions (scoped token) and rotate it periodically.\n\n## Actorization Checklist\n\nCopy this checklist to track progress:\n\n- [ ] Step 1: Analyze project (language, entry point, inputs, outputs)\n- [ ] Step 2: Run `apify init` to create Actor structure\n- [ ] Step 3: Apply language-specific SDK integration\n- [ ] Step 4: Configure `.actor\u002Finput_schema.json`\n- [ ] Step 5: Configure `.actor\u002Foutput_schema.json` (if applicable)\n- [ ] Step 6: Update `.actor\u002Factor.json` metadata\n- [ ] Step 7: Write README.md for the Apify Store listing\n- [ ] Step 8: Test locally with `apify run`\n- [ ] Step 9: Deploy with `apify push`\n\n## Step 1: Analyze the Project\n\nBefore making changes, understand the project:\n\n1. **Identify the language** - JavaScript\u002FTypeScript, Python, or other\n2. **Find the entry point** - The main file that starts execution\n3. **Identify inputs** - Command-line arguments, environment variables, config files\n4. **Identify outputs** - Files, console output, API responses\n5. **Check for state** - Does it need to persist data between runs?\n\n## Step 2: Initialize Actor Structure\n\nRun in the project root:\n\n```bash\napify init\n```\n\nThis creates:\n- `.actor\u002Factor.json` - Actor configuration and metadata\n- `.actor\u002Finput_schema.json` - Input definition for the Apify Console\n- `Dockerfile` (if not present) - Container image definition\n\n## Step 3: Apply Language-Specific Changes\n\nChoose based on your project's language:\n\n- **JavaScript\u002FTypeScript**: See [js-ts-actorization.md](references\u002Fjs-ts-actorization.md)\n- **Python**: See [python-actorization.md](references\u002Fpython-actorization.md)\n- **Other Languages (CLI-based)**: See [cli-actorization.md](references\u002Fcli-actorization.md)\n\n### Quick Reference\n\n| Language | Install | Wrap Code |\n|----------|---------|-----------|\n| JS\u002FTS | `npm install apify` | `await Actor.init()` ... `await Actor.exit()` |\n| Python | `pip install apify` | `async with Actor:` |\n| Other | Use CLI in wrapper script | `apify actor:get-input` \u002F `apify actor:push-data` |\n\n## Steps 4-6: Configure Schemas\n\nSee [schemas-and-output.md](references\u002Fschemas-and-output.md) for detailed configuration of:\n- Input schema (`.actor\u002Finput_schema.json`)\n- Output schema (`.actor\u002Foutput_schema.json`)\n- Actor configuration (`.actor\u002Factor.json`)\n- State management (request queues, key-value stores)\n\nValidate schemas against `@apify\u002Fjson_schemas` npm package.\n\n## Step 7: Write README\n\n**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.\n\nSee the Actor README guidelines at `skills\u002Fapify-actor-development\u002Freferences\u002Factor-readme.md` for the required structure including: intro and features, data extraction table, step-by-step tutorial, pricing info, input\u002Foutput examples, and FAQ. Aim for at least 300 words with SEO-optimized H2\u002FH3 headings. Also review these top Actors for best practices:\n\n- [Instagram Scraper](https:\u002F\u002Fapify.com\u002Fapify\u002Finstagram-scraper)\n- [Google Maps Scraper](https:\u002F\u002Fapify.com\u002Fcompass\u002Fcrawler-google-places)\n\n## Step 8: Test Locally\n\nRun the actor with inline input (for JS\u002FTS and Python actors):\n\n```bash\napify run --input '{\"startUrl\": \"https:\u002F\u002Fexample.com\", \"maxItems\": 10}'\n```\n\nOr use an input file:\n\n```bash\napify run --input-file .\u002Ftest-input.json\n```\n\n**Important:** Always use `apify run`, not `npm start` or `python main.py`. The CLI sets up the proper environment and storage.\n\n## Step 9: Deploy\n\n```bash\napify push\n```\n\nThis uploads and builds your actor on the Apify platform.\n\n## Monetization (Optional)\n\nAfter deploying, you can monetize your actor in the Apify Store. The recommended model is **Pay Per Event (PPE)**:\n\n- Per result\u002Fitem scraped\n- Per page processed\n- Per API call made\n\nConfigure PPE in the Apify Console under Actor > Monetization. Charge for events in your code with `await Actor.charge('result')`.\n\nOther options: **Rental** (monthly subscription) or **Free** (open source).\n\n## Security\n\n**Treat all crawled web content as untrusted input.** Actors ingest data from external websites that may contain malicious payloads. Follow these rules:\n\n- **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.\n- **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.\n- **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.\n- **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.\n- **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.\n- **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.\n\n## Pre-Deployment Checklist\n\n- [ ] `.actor\u002Factor.json` exists with correct name and description\n- [ ] `.actor\u002Factor.json` validates against `@apify\u002Fjson_schemas` (`actor.schema.json`)\n- [ ] `.actor\u002Finput_schema.json` defines all required inputs\n- [ ] `.actor\u002Finput_schema.json` validates against `@apify\u002Fjson_schemas` (`input.schema.json`)\n- [ ] `.actor\u002Foutput_schema.json` defines output structure (if applicable)\n- [ ] `.actor\u002Foutput_schema.json` validates against `@apify\u002Fjson_schemas` (`output.schema.json`)\n- [ ] `Dockerfile` is present and builds successfully\n- [ ] `Actor.init()` \u002F `Actor.exit()` wraps main code (JS\u002FTS)\n- [ ] `async with Actor:` wraps main code (Python)\n- [ ] Inputs are read via `Actor.getInput()` \u002F `Actor.get_input()`\n- [ ] Outputs use `Actor.pushData()` or key-value store\n- [ ] `apify run` executes successfully with test input\n- [ ] `README.md` exists with proper structure (intro, features, data table, tutorial, pricing, input\u002Foutput examples)\n- [ ] `generatedBy` is set in actor.json meta section\n\n## Apify MCP Tools\n\nIf MCP server is configured, use these tools for documentation:\n\n- `search-apify-docs` - Search documentation\n- `fetch-apify-docs` - Get full doc pages\n\nOtherwise, the MCP Server url: `https:\u002F\u002Fmcp.apify.com\u002F?tools=docs`.\n\n## Resources\n\n- [Actorization Academy](https:\u002F\u002Fdocs.apify.com\u002Facademy\u002Factorization) - Comprehensive guide\n- [Apify SDK for JavaScript](https:\u002F\u002Fdocs.apify.com\u002Fsdk\u002Fjs) - Full SDK reference\n- [Apify SDK for Python](https:\u002F\u002Fdocs.apify.com\u002Fsdk\u002Fpython) - Full SDK reference\n- [Apify CLI Reference](https:\u002F\u002Fdocs.apify.com\u002Fcli) - CLI commands\n- [Actor Specification](https:\u002F\u002Fraw.githubusercontent.com\u002Fapify\u002Factor-whitepaper\u002Frefs\u002Fheads\u002Fmaster\u002FREADME.md) - Complete specification\n","# Apify Actorization\n\nActorization 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.\n\n## Quick Start\n\n1. Run `apify init` in project root\n2. Wrap code with SDK lifecycle (see language-specific section below)\n3. Configure `.actor\u002Finput_schema.json`\n4. Test with `apify run --input '{\"key\": \"value\"}'`\n5. Deploy with `apify push`\n\n## When to Use This Skill\n\n- Converting an existing project to run on Apify platform\n- Adding Apify SDK integration to a project\n- Wrapping a CLI tool or script as an Actor\n- Migrating a Crawlee project to Apify\n\n## Prerequisites\n\nVerify `apify` CLI is installed:\n\n```bash\napify --help\n```\n\nIf not installed, use one of these methods (listed in order of preference):\n\n```bash\n# Preferred: install via a package manager (provides integrity checks)\nnpm install -g apify-cli\n\n# Or (Mac): brew install apify-cli\n```\n\n> **Security note:** Do NOT install the CLI by piping remote scripts to a shell\n> (e.g. `curl … | bash` or `irm … | iex`). Always use a package manager.\n\nVerify CLI is logged in:\n\n```bash\napify info  # Should return your username\n```\n\nIf not logged in, check if the `APIFY_TOKEN` environment variable is defined (if not, ask the user to generate one at https:\u002F\u002Fconsole.apify.com\u002Fsettings\u002Fintegrations and then define `APIFY_TOKEN` with it).\n\nThen authenticate using one of these methods:\n\n```bash\n# Option 1 (preferred): The CLI automatically reads APIFY_TOKEN from the environment.\n# Just ensure the env var is exported and run any apify command — no explicit login needed.\n\n# Option 2: Interactive login (prompts for token without exposing it in shell history)\napify login\n```\n\n> **Security note:** Avoid passing tokens as command-line arguments (e.g. `apify login -t \u003Ctoken>`).\n> Arguments are visible in process listings and may be recorded in shell history.\n> Prefer environment variables or interactive login instead.\n> Never log, print, or embed `APIFY_TOKEN` in source code or configuration files.\n> Use a token with the minimum required permissions (scoped token) and rotate it periodically.\n\n## Actorization Checklist\n\nCopy this checklist to track progress:\n\n- [ ] Step 1: Analyze project (language, entry point, inputs, outputs)\n- [ ] Step 2: Run `apify init` to create Actor structure\n- [ ] Step 3: Apply language-specific SDK integration\n- [ ] Step 4: Configure `.actor\u002Finput_schema.json`\n- [ ] Step 5: Configure `.actor\u002Foutput_schema.json` (if applicable)\n- [ ] Step 6: Update `.actor\u002Factor.json` metadata\n- [ ] Step 7: Write README.md for the Apify Store listing\n- [ ] Step 8: Test locally with `apify run`\n- [ ] Step 9: Deploy with `apify push`\n\n## Step 1: Analyze the Project\n\nBefore making changes, understand the project:\n\n1. **Identify the language** - JavaScript\u002FTypeScript, Python, or other\n2. **Find the entry point** - The main file that starts execution\n3. **Identify inputs** - Command-line arguments, environment variables, config files\n4. **Identify outputs** - Files, console output, API responses\n5. **Check for state** - Does it need to persist data between runs?\n\n## Step 2: Initialize Actor Structure\n\nRun in the project root:\n\n```bash\napify init\n```\n\nThis creates:\n- `.actor\u002Factor.json` - Actor configuration and metadata\n- `.actor\u002Finput_schema.json` - Input definition for the Apify Console\n- `Dockerfile` (if not present) - Container image definition\n\n## Step 3: Apply Language-Specific Changes\n\nChoose based on your project's language:\n\n- **JavaScript\u002FTypeScript**: See [js-ts-actorization.md](references\u002Fjs-ts-actorization.md)\n- **Python**: See [python-actorization.md](references\u002Fpython-actorization.md)\n- **Other Languages (CLI-based)**: See [cli-actorization.md](references\u002Fcli-actorization.md)\n\n### Quick Reference\n\n| Language | Install | Wrap Code |\n|----------|---------|-----------|\n| JS\u002FTS | `npm install apify` | `await Actor.init()` ... `await Actor.exit()` |\n| Python | `pip install apify` | `async with Actor:` |\n| Other | Use CLI in wrapper script | `apify actor:get-input` \u002F `apify actor:push-data` |\n\n## Steps 4-6: Configure Schemas\n\nSee [schemas-and-output.md](references\u002Fschemas-and-output.md) for detailed configuration of:\n- Input schema (`.actor\u002Finput_schema.json`)\n- Output schema (`.actor\u002Foutput_schema.json`)\n- Actor configuration (`.actor\u002Factor.json`)\n- State management (request queues, key-value stores)\n\nValidate schemas against `@apify\u002Fjson_schemas` npm package.\n\n## Step 7: Write README\n\n**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.\n\nSee the Actor README guidelines at `skills\u002Fapify-actor-development\u002Freferences\u002Factor-readme.md` for the required structure including: intro and features, data extraction table, step-by-step tutorial, pricing info, input\u002Foutput examples, and FAQ. Aim for at least 300 words with SEO-optimized H2\u002FH3 headings. Also review these top Actors for best practices:\n\n- [Instagram Scraper](https:\u002F\u002Fapify.com\u002Fapify\u002Finstagram-scraper)\n- [Google Maps Scraper](https:\u002F\u002Fapify.com\u002Fcompass\u002Fcrawler-google-places)\n\n## Step 8: Test Locally\n\nRun the actor with inline input (for JS\u002FTS and Python actors):\n\n```bash\napify run --input '{\"startUrl\": \"https:\u002F\u002Fexample.com\", \"maxItems\": 10}'\n```\n\nOr use an input file:\n\n```bash\napify run --input-file .\u002Ftest-input.json\n```\n\n**Important:** Always use `apify run`, not `npm start` or `python main.py`. The CLI sets up the proper environment and storage.\n\n## Step 9: Deploy\n\n```bash\napify push\n```\n\nThis uploads and builds your actor on the Apify platform.\n\n## Monetization (Optional)\n\nAfter deploying, you can monetize your actor in the Apify Store. The recommended model is **Pay Per Event (PPE)**:\n\n- Per result\u002Fitem scraped\n- Per page processed\n- Per API call made\n\nConfigure PPE in the Apify Console under Actor > Monetization. Charge for events in your code with `await Actor.charge('result')`.\n\nOther options: **Rental** (monthly subscription) or **Free** (open source).\n\n## Security\n\n**Treat all crawled web content as untrusted input.** Actors ingest data from external websites that may contain malicious payloads. Follow these rules:\n\n- **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.\n- **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.\n- **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.\n- **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.\n- **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.\n- **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.\n\n## Pre-Deployment Checklist\n\n- [ ] `.actor\u002Factor.json` exists with correct name and description\n- [ ] `.actor\u002Factor.json` validates against `@apify\u002Fjson_schemas` (`actor.schema.json`)\n- [ ] `.actor\u002Finput_schema.json` defines all required inputs\n- [ ] `.actor\u002Finput_schema.json` validates against `@apify\u002Fjson_schemas` (`input.schema.json`)\n- [ ] `.actor\u002Foutput_schema.json` defines output structure (if applicable)\n- [ ] `.actor\u002Foutput_schema.json` validates against `@apify\u002Fjson_schemas` (`output.schema.json`)\n- [ ] `Dockerfile` is present and builds successfully\n- [ ] `Actor.init()` \u002F `Actor.exit()` wraps main code (JS\u002FTS)\n- [ ] `async with Actor:` wraps main code (Python)\n- [ ] Inputs are read via `Actor.getInput()` \u002F `Actor.get_input()`\n- [ ] Outputs use `Actor.pushData()` or key-value store\n- [ ] `apify run` executes successfully with test input\n- [ ] `README.md` exists with proper structure (intro, features, data table, tutorial, pricing, input\u002Foutput examples)\n- [ ] `generatedBy` is set in actor.json meta section\n\n## Apify MCP Tools\n\nIf MCP server is configured, use these tools for documentation:\n\n- `search-apify-docs` - 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