How does it handle different environments?

It uses a storage abstraction that automatically switches between production Netlify Blobs and local JSON mock files based on environment variables.

How are scheduled updates managed with this skill?

Tasks are defined in tasks.ts using a single source of truth for keys and organized into DAILY or HOURLY tuples for Trigger.dev execution.

What is the core purpose of the Data Layer skill?

The skill provides a standardized framework for fetching, transforming, and caching external data to ensure architectural consistency across the ethereum.org codebase.

Where should data transformation logic be placed?

According to the skill rules, all data transformations must occur within the fetchers in src/data-layer/fetchers/, keeping the public getters in index.ts as pure passthroughs.

Data Layer Architecture Management

Name: Data Layer Architecture Management
Author: ethereum

byethereum

•

5,837

API Development

Standardizes the implementation of data fetching, caching, and storage patterns for complex Next.js applications.

About

This skill provides specialized guidance for working within the ethereum.org data-layer architecture, ensuring consistency when managing external data sources. It facilitates the creation of standardized fetchers, centralized task keys for Trigger.dev, and storage abstractions that toggle between production Netlify Blobs and local mock files. By enforcing architectural rules such as pure passthrough getters and cached wrappers, it helps developers maintain a scalable and performant data pipeline for high-traffic documentation and resource sites.

Key Features

Seamless storage abstraction between Netlify Blobs and local mocks
5,837 GitHub stars
Standardized fetcher and transformer implementation patterns
Centralized task management for Trigger.dev schedules
Automated workflow for adding new external data sources
Next.js caching adapter integration for optimized data retrieval

Use Cases

Setting up local development environments with mock data to reduce API dependency
Integrating a new external API or data source into the ethereum.org website
Configuring scheduled data updates for metrics like ETH price or L2 statistics

About

Key Features

Seamless storage abstraction between Netlify Blobs and local mocks
5,837 GitHub stars
Standardized fetcher and transformer implementation patterns
Centralized task management for Trigger.dev schedules
Automated workflow for adding new external data sources
Next.js caching adapter integration for optimized data retrieval

Use Cases

Setting up local development environments with mock data to reduce API dependency
Integrating a new external API or data source into the ethereum.org website
Configuring scheduled data updates for metrics like ETH price or L2 statistics