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store-longevity-radar

Extract long-lived Korean retail stores by matching public commercial district snapshots across years.

7.4k|904|Updated Mar 24, 2026
Search Tags:#korea#public data#Market Research#store matching#snapshot analysis#csv extraction#commercial district
One-click install
npx skills add https://github.com/NomaDamas/k-skill --skill store-longevity-radar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: store-longevity-radar
Source: https://github.com/NomaDamas/k-skill/tree/main/store-longevity-radar
Command: npx skills add https://github.com/NomaDamas/k-skill --skill store-longevity-radar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Finding stores that have survived for many years (e.g., old stationery shops, hardware stores) is hard because public business data lacks founding dates and business registration numbers. This Skill uses the unauthenticated public snapshot files from the Small Enterprise and Market Service commercial district dataset to enumerate all stores matching industry codes or name keywords, then matches them against a past snapshot CSV by store ID or name+coordinates to list stores that existed years ago and are still operating.

Core Features & Use Cases

  • Current snapshot extraction (current): Downloads the latest quarterly nationwide ZIP (17 provinces, unauthenticated) and filters stores by industry subcategory codes and name keywords, with optional province filtering and 1-day local caching.
  • Longevity matching (match): Matches current results against a user-supplied past snapshot CSV via store ID or normalized name plus coordinate distance (default 150m), automatically including legacy industry codes for stationery/toy categories.
  • Verified mirror fallback: If the direct data.go.kr download fails, falls back to a SHA-256 and size-verified R2 mirror before promoting files to cache.
  • Use Case: Ask for a list of stationery stores in Seoul and Busan that already existed in a 2019 snapshot and are still open today, exported as a CSV.

Quick Start

Ask the AI to run the store-longevity-radar current command to extract all stationery and toy stores nationwide into a CSV, then run match with your past snapshot CSV to list long-lived stores.

Frequently Asked Questions about store-longevity-radar

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

FAQPage Schema
How do I find long-lived stores in Korea using public data?▼

Download the latest commercial district snapshot from data.go.kr, extract stores by industry code or name keyword, then match against a past snapshot CSV using store ID or normalized name plus coordinates within 150 meters. Stores present in both snapshots are reported as long-lived.

How to extract all stores of a specific industry from Korean commercial district data?▼

Run the current subcommand with the industry subcategory code (e.g., G21302 for stationery retail) or name keywords. The script downloads the latest quarterly ZIP covering all 17 provinces and outputs matching stores with addresses and coordinates as CSV or JSON.

Does the commercial district dataset include business registration numbers or opening dates?▼

No. The dataset contains no business registration numbers or founding dates, so results represent the earliest observed snapshot point, not the actual opening date. For closure confirmation use the National Tax Service status lookup, and for licensed businesses check local licensing records.

What happens when the data.go.kr download fails or times out?▼

The script automatically falls back to a verified public mirror on R2. The mirror ZIP is only cached after its size and SHA-256 match the manifest and the ZIP passes integrity and CSV presence checks; otherwise an unavailable status with both error causes is returned.

Why does matching against an old snapshot return zero results?▼

Zero matches usually mean the industry code system changed between snapshots. Retry using only name keywords, or supply both the current and legacy industry codes together; the helper auto-includes legacy codes for the default stationery and toy categories.

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