apify/agent-skills9 files

Apify Actor Development

Develop, debug, and deploy Apify Actors - serverless cloud programs for web scraping, automation, and data processing. Use when creating new Actors, modifying existing ones, or troubleshooting Actor code.

Specification
Skill ID
apify/agent-skills/apify-actor-development
Publisher
apify
Repository
agent-skills
Installs
0
Files
9
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

apify/agent-skills/apify-actor-developmentInstalls these files
  • SKILL.md
  • references/actor-json.md
  • references/actor-readme.md
  • references/dataset-schema.md
  • references/input-schema.md
  • references/key-value-store-schema.md
  • references/logging.md
  • references/output-schema.md
  • references/standby-mode.md

What this skill tells the agent

Apify Actor development

Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.

What are Apify Actors?

Actors are serverless programs inspired by the UNIX philosophy - programs that do one thing well and can be easily combined to build complex systems. They're packaged as Docker images and run in isolated containers in the cloud.

Core Concepts:

  • Accept well-defined JSON input
  • Perform isolated tasks (web scraping, automation, data processing)
  • Produce structured JSON output to datasets and/or store data in key-value stores
  • Can run from seconds to hours or even indefinitely
  • Persist state and can be restarted

Prerequisites and setup (mandatory)

Before creating or modifying Actors, verify that apify CLI is installed apify --help.

If it is 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.

When the apify CLI is installed, check that it is logged in with:

apify info  # Should return your username

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

apify login

If browser login isn't available (headless environment or CI), the CLI automatically reads APIFY_TOKEN from the environment. Ensure the env var is exported and run any apify command - 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 environment variables or interactive login instead. Never log, print, or embed APIFY_TOKEN in source code or configuration files. Use a token with the minimum required permissions (scoped token) and rotate it periodically.

Telemetry attribution (required)

Pass --user-agent apify-agent-skills/apify-actor-development on every apify command you run from this skill - apify create, apify run, apify push, apify call, and the rest. It is a global flag accepted by all apify commands; it only tags the call for telemetry attribution and changes nothing else.

apify push --user-agent apify-agent-skills/apify-actor-development

Template selection

IMPORTANT: Before starting Actor development, always ask the user which programming language they prefer:

  • JavaScript - Use apify create <actor-name> -t project_empty --user-agent apify-agent-skills/apify-actor-development
  • TypeScript - Use apify create <actor-name> -t ts_empty --user-agent apify-agent-skills/apify-actor-development
  • Python - Use apify create <actor-name> -t python-empty --user-agent apify-agent-skills/apify-actor-development

Use the appropriate CLI command based on the user's language choice. Additional packages (Crawlee, Playwright, etc.) can be installed later as needed.

Quick start workflow

  1. Create Actor project - Run the appropriate apify create command based on user's language preference (see Template selection above)
  2. Install dependencies (verify package names match intended packages before installing)
  • JavaScript/TypeScript: npm install (uses package-lock.json for reproducible, integrity-checked installs — commit the lockfile to version control)
  • Python: pip install -r requirements.txt (pin exact versions in requirements.txt, e.g. crawlee==1.2.3, and commit the file to version control)
  1. Implement logic - Write the Actor code in src/main.py, src/main.js, or src/main.ts
  2. Configure schemas - Update input/output schemas in .actor/input_schema.json, .actor/output_schema.json, .actor/dataset_schema.json
  3. Configure platform settings - Update .actor/actor.json with Actor metadata (see references/actor-json.md)
  4. Write documentation - Create comprehensive README.md for the marketplace (see references/actor-readme.md — this is mandatory, not optional)
  5. Test locally - Run apify run --user-agent apify-agent-skills/apify-actor-development to verify functionality (see Local testing section below)
  6. Deploy - Run apify push --user-agent apify-agent-skills/apify-actor-development to deploy the Actor on the Apify platform (Actor name is defined in .actor/actor.json)

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.

Best practices

✓ Do:

  • Use apify run to test Actors locally (configures Apify environment and storage)
  • Use Apify SDK (apify) for code running on the Apify platform
  • Validate input early with proper error handling and fail gracefully
  • Use CheerioCrawler for static HTML (10x faster than browsers)
  • Use PlaywrightCrawler only for JavaScript-heavy sites
  • Use router pattern (createCheerioRouter/createPlaywrightRouter) for complex crawls
  • Implement retry strategies with exponential backoff
  • Use proper concurrency: HTTP (10-50), Browser (1-5)
  • Set sensible defaults in .actor/input_schema.json
  • Define output schema in .actor/output_schema.json
  • Clean and validate data before pushing to dataset
  • Use semantic CSS selectors with fallback strategies
  • Respect robots.txt, ToS, and implement rate limiting
  • Always use `apify/log` package — censors sensitive data (API keys, tokens, credentials)
  • Implement readiness probe handler (required if your Actor uses standby mode)

✗ Don't:

  • Use npm start, npm run start, npx apify run, or similar commands to run Actors (use apify run instead)
  • Assume local storage from apify run is pushed to or visible in Apify Console — it is local-only; deploy with apify push and run on the platform to see results in Apify Console
  • Rely on Dataset.getInfo() for final counts on Cloud
  • Use browser crawlers when HTTP/Cheerio works
  • Hard code values that should be in input schema or environment variables
  • Skip input validation or error handling

Use this skill in a project

Open any RiverX project, search the Skills panel for apify/agent-skills/apify-actor-development, and install it in one click.

Use this skill