스킬 address-normalize

📦

address-normalize

Name: address-normalize
Author: tahodev

콘텐츠 리비전 r1 낮은 위험 🌐 네트워크 접근📁 파일 시스템 접근⚙️ 외부 명령어

Normalize Japanese Addresses with Public ABR Data

Japanese addresses contain inconsistent numerals and omitted administrative names. This skill uses public ABR masters to identify address components and codes while preserving the remaining text.

지원: Claude Codex Code(CC)

📊 74 적절함

Maintain this Skill? Claim it 📊 74 적절함

내 에이전트로 설치

이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.

에이전트 요청

Review the Skillstore skill "address-normalize" from https://skillstore.io/skills/tahodev-address-normalize.md and its manifest at https://skillstore.io/api/skills/tahodev-address-normalize/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

에이전트가 읽기 쉬운 리소스

AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.

Markdown 상세 GET /skills/tahodev-address-normalize.md 서명된 manifest GET /api/skills/tahodev-address-normalize/manifest 서명된 lockfile GET /api/skills/tahodev-address-normalize/lockfile

테스트해 보기

"address-normalize" 사용 중입니다. Normalize 東京都千代田区内幸町1丁目1-1.

예상 결과:

Prefecture: Tokyo. Municipality: Chiyoda.
Town: Uchisaiwaicho, chome 1. Municipality code: 131016. Town identifier: 0001001.
Remaining text: 1-1. The administrative and town components matched; the street number was not validated.

"address-normalize" 사용 중입니다. Normalize 新宿区歌舞伎町一丁目4-1.

예상 결과:

Prefecture: Tokyo, inferred from Shinjuku municipality.
Town: Kabukicho, chome 1. The kanji numeral matched the town master.
Remaining text: 4-1. Street-level validation is outside this result.

"address-normalize" 사용 중입니다. Normalize 東京都千代田区内幸町 without a chome.

예상 결과:

Prefecture: Tokyo. Municipality: Chiyoda.
No town match was selected because the candidate records require a chome.
Remaining text: 内幸町. Review the missing chome before accepting the address.

보안 감사

낮은 위험

v1 • 2026. 10. 13. 버전별 보고서 열기

Most static alerts are false positives from Markdown, public data URLs, and scoped cache access. Three findings identify one unbounded download and ZIP decompression risk; a semantic finding identifies abolished-record acceptance. No evidence found of prompt injection, credential access, address exfiltration, or malicious intent.

스캔된 파일

320

분석된 줄 수

검토 항목

오탐 무시됨

확인된 보안 우려 사항 (1)

낮음

lookup.py:31-32 lookup.py:65-88 SKILL.md:40

Abolished records remain eligible for current-address matches

The documentation requires excluding records with ablt_date, but the helper loads and matches every row. Retired administrative or town records can receive successful matches.

The loader and matching code never check ablt_date, although the documentation explicitly requires it. This establishes a data-integrity defect, not malicious intent.

기능 검토 항목 (3)

이 스킬에 대해 예상될 수 있는 실제 로컬 기능이므로 검토가 필요하지만, 확인된 악의적 동작으로는 집계되지 않습니다.

중간

lookup.py:28

Fetch API call

z = zipfile.ZipFile(io.BytesIO(fetch(url)))

This loads the entire downloaded archive into memory without a byte cap. An oversized upstream response could exhaust memory despite the request timeout.

중간

lookup.py:20

Python HTTP libraries

with urllib.request.urlopen(req, timeout=timeout) as r:

The response is immediately consumed through unrestricted r.read() on line 21. A timeout does not bound memory consumption from an oversized response.

중간

lookup.py:28

Python archive libraries

z = zipfile.ZipFile(io.BytesIO(fetch(url)))

The archive member is decompressed through unrestricted z.read(inner) on line 30. A highly compressed oversized member could exhaust memory or disk.

위험 요인

감사자: codex

이 보고서 공유 및 인용

버전이 지정된 평가 보고서, 중립 배지, 임베드 카드 및 인용을 공유하세요. Skillstore는 근거를 보고하지만 이 Skill의 안전 여부를 판단하지 않습니다.

버전별 보고서 열기

보고서 링크 복사

https://skillstore.io/skills/tahodev-address-normalize/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![Skillstore security assessment](https://skillstore.io/badges/skills/tahodev-address-normalize/security.svg)](https://skillstore.io/skills/tahodev-address-normalize?utm_source=security_passport_badge)

HTML 배지

<a href="https://skillstore.io/skills/tahodev-address-normalize?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/tahodev-address-normalize/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

임베드 카드

<iframe src="https://skillstore.io/embed/skills/tahodev-address-normalize.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

학술 인용 (APA · BibTeX · CFF)

APA 인용

tahodev. (2026). address-normalize security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/tahodev-address-normalize/audits/1

BibTeX 인용

@techreport{tahodev-tahodev-address-normalize-2026,
  author = {tahodev},
  title = {address-normalize security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/tahodev-address-normalize/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "address-normalize security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "tahodev"
date-released: "2026-10-13"
url: "https://skillstore.io/skills/tahodev-address-normalize/audits/1"
identifiers:
  - type: other
    value: "skillstore:tahodev-address-normalize:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간

아키텍처

유지보수성

콘텐츠

커뮤니티

사양 준수

만들 수 있는 것

Prepare customer address records

Separate administrative components and identifiers before reviewing unmatched or ambiguous customer addresses.

Explore municipal town masters

List towns for a selected prefecture and compare keyword results with the published ABR records.

Prototype an address import workflow

Use the Python helper to extract structured address fields before adding current-record filtering and application-specific validation.

이 프롬프트를 사용해 보세요

Parse one address

Normalize 東京都千代田区内幸町1丁目1-1 with this skill. Present the prefecture, municipality, town, identifiers, and remaining text in plain language.

Compare numeral variants

Compare 新宿区歌舞伎町一丁目4-1 and 新宿区歌舞伎町１丁目4-1. Show whether the town identifiers match and retain each remaining address portion.

Find town candidates

List Tokyo town records with prefecture code 13 and keyword 歌舞伎. Present municipality codes, town identifiers, and labels without claiming delivery validation.

Review an address import

Review these addresses: [address list]. Check ambiguous municipalities, abolished records, missing chome, and cache age. Separate reliable matches from unresolved entries.

모범 사례

Refresh masters when freshness matters, then independently exclude abolished records and verify ambiguous municipality matches.
Review unmatched results and remaining text before importing records or using them for operational decisions.
Attribute the Digital Agency's Address Base Registry and follow the documented data licensing terms.

피하기

Treating a successful town match as proof that a street number exists or that an address is deliverable.
Assuming --pref constrains address parsing or that omitted prefectures always produce an unambiguous municipality.
Using cached or abolished records as current authoritative addresses without reviewing master dates and status fields.

자주 묻는 질문

Which assistants can use this skill?

The report lists Claude, Codex, and Claude Code. Running the included helper requires an environment with Python 3.

Does it require an API key or account?

No. The helper downloads public ABR master files without credentials.

Are input addresses sent to a remote service?

The helper matches addresses locally. Its requests download public masters and do not include the input address.

Can it work offline?

Yes, when all required master CSV files are already cached. Initial downloads and requested refreshes require network access.

Does it validate street numbers or return coordinates?

No. Street numbers and building details remain outside its normalization scope. Geocoding requires a separate tool.

Does it guarantee a current, unambiguous address match?

No. The helper does not exclude abolished records or reject ambiguous municipalities. The --pref option selects town-list data but does not constrain address parsing.