address-mapping

Normalize raw location strings into standardized address schemas with country codes.

Updated Jan 7, 2025
One-click install
npx skills add https://github.com/jobstash/webapp --skill address-mapping
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: address-mapping
Source: https://github.com/jobstash/webapp/tree/main/.claude/skills/address-mapping
Command: npx skills add https://github.com/jobstash/webapp --skill address-mapping

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill standardizes raw, often inconsistent, location strings into structured, machine-readable address formats, ensuring data consistency and compliance with schema requirements.

Core Features & Use Cases

  • Location Normalization: Converts various location inputs (cities, countries, regions, remote indicators) into a defined address schema.
  • Remote Work Handling: Correctly identifies and formats remote work locations.
  • Use Case: When processing job postings, use this Skill to ensure all location data, whether it's "NYC", "[REMOTE] Singapore", or "USA, UK", is converted into a consistent format for display and analysis.

Quick Start

Use the address-mapping skill to convert the location string "Chicago, IL / NY, US - Remote (any location)".

Frequently Asked Questions about address-mapping

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

FAQPage Schema
How do I standardize raw location strings for data cleaning?

To standardize raw location strings for data cleaning, you normalize inconsistent inputs like cities or regions into a structured address schema with country codes and locality details.

Can I use address mapping to handle remote work indicators in location data?

Yes, address mapping handles remote work indicators by correctly identifying and formatting remote work locations within the standardized address schema.

What is the best way to structure diverse location inputs into a consistent schema?

The best way to structure diverse location inputs is mapping them to a consistent schema that enforces address standardization rules, ensuring data consistency for location-based services.

Does address mapping support multiple regional expansions in a single string?

Address mapping supports regional expansions by parsing multiple locations within a single input string and mapping them to the defined address schema with appropriate country codes.

Are there limitations when processing large batches of location strings?

Yes, a limitation when processing location strings is the requirement to adhere to maximum address count rules, meaning batches must conform to defined schema constraints.