Agent skill · software engineering · jeremylongshore
apify-reference-architecture
Production-grade architecture patterns for Apify-powered applications. Use when designing scraping infrastructure, building multi-Actor pipelines, or integrating Apify into a larger system architecture. Trigger with "apify architecture", "apify best practices", "apify project structure", "scraping architecture", "apify system design".
Why this skill is useful
Provides specific architecture patterns and implementation details for building Apify applications that the AI wouldn't reliably generate on its own.
What it needs
Requires apify-cli, node installed locally. Requires apify account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Apify Reference Architecture Overview Production-ready architecture patterns for applications built on Apify. Three patterns scale from a single scraper to a full-stack integration: 1. Standalone Actor — one scraper deployed to the Apify platform. 2. Multi-Actor Pipeline — a discover → scrape → transform chain of Actors. 3. Full-Stack Integration — an application using Apify as a data source behind a service layer. This skill helps you choose the right pattern, lay out the directory structure, and wire the skeleton code. Full directory trees, diagrams, and code for every pattern live in references/architecture-patterns.md; the service layer, configuration loader, and health check live in references/implementation.md. Prerequisites Runtime: Node.js >=18, TypeScript, and the Apify CLI (npm i -g apify-cli). Packages: apify + crawlee (inside an Actor), apify-client (calling Actors from an app), zod (input validation). Auth: an Apify API token. Set APIFYTOKEN in the environment; the Apify SDK and apify-client read it automatically (or pass it explicitly to new ApifyClient({ token })). Never hardcode the token — inject it via env var and validate at startup. Access: Read and Grep the target repository so you can match the recommended layout against the code already on disk before proposing changes. Instructions 1. Pick the pattern. One scraper → Pattern 1. A staged workflow that discovers, scrapes, then cleans → Pattern 2. An app that consumes scraped data → Pattern 3. 2. Grep the existing repo for apify, apify-client, and Actor.main to see what is already wired, so you extend rather than duplicate structure. 3. Lay out the directory from the pattern's tree in references/architecture-patterns.md. Keep routing, extraction, and validation in separate modules. 4. Add typed input validation with zod (see src/types.ts in the reference) so bad input fails fast at the Actor boundary instead of mid-crawl. 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/apify-reference-architecture