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OntoLedgy
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javascript-data-engineer

Enforce TypeScript type safety and JS/TS best practices in data pipelines.

Updated Aug 23, 2026
Search Tags:#typescript#javascript#type-safety#code-review#data-engineering#clean-code#async-patterns
One-click install
npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill javascript-data-engineer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: javascript-data-engineer
Source: https://github.com/OntoLedgy/ol_ai_context_library/tree/main/skills/javascript-data-engineer
Command: npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill javascript-data-engineer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates the risk of inconsistent, error-prone JavaScript/TypeScript data engineering work by enforcing language-specific best practices for type safety, async patterns, naming conventions, and tooling, ensuring implementations are maintainable, compliant, and production-ready.

Core Features & Use Cases

  • JS/TS-Specific Implementation Guidance: Extends the base data-engineer skill with TypeScript type system rules, async/await patterns, module conventions, and tooling (eslint, prettier, vitest/jest, tsc) tailored to JavaScript and TypeScript data workflows.
  • Code Review & Migration Support: Reviews existing JS/TS data code for clean-coding compliance, and provides clear rules for migrating legacy plain JavaScript modules to TypeScript.
  • Smart Routing: Automatically routes frontend/UI JavaScript/TypeScript work (React, Vue, Angular) to the ui-engineer skill, and standalone clean-code violation scans to the clean-code-reviewer skill to ensure the right tool is used for each task.

Quick Start

Use the javascript-data-engineer skill to build a type-safe, fully linted TypeScript data pipeline that ingests CSV transaction records, validates them with custom typed errors, and writes the processed results to a PostgreSQL database, following all project tooling and naming conventions.

Frequently Asked Questions about javascript-data-engineer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a type-safe TypeScript data pipeline for ingesting and processing records?▼

Building a type-safe TypeScript data pipeline involves enforcing strict type checking, applying proper async/await patterns, and using tooling like eslint and vitest to ensure your data workflows are maintainable and production-ready.

What is the best way to migrate legacy JavaScript modules to TypeScript?▼

Migrating legacy JavaScript modules to TypeScript requires applying clear rules for type safety, updating module conventions, and ensuring adherence to language-specific clean code standards for a compliant transition.

How do I review existing JavaScript data engineering code for clean code compliance?▼

Reviewing existing JavaScript data engineering code for compliance involves scanning for type safety, proper async patterns, and adherence to JS/TS naming and module conventions to eliminate error-prone implementations.

Can I use this for frontend React or Angular TypeScript work?▼

For frontend UI JavaScript or TypeScript work involving React, Vue, or Angular, tasks are automatically routed to the ui-engineer skill to ensure the right tool is used for the job.

Does TypeScript data engineering work require custom typed errors for validation?▼

TypeScript data engineering requires proper error handling with typed custom errors to validate records and eliminate inconsistent, error-prone implementations in your data pipelines.

When should I use a standalone clean-code violation scan instead of a full data pipeline review?▼

Standalone clean-code violation scans are routed to the clean-code-reviewer skill, while the data engineering approach is used when building APIs, libraries, or pipelines requiring strict TypeScript type checking.

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