Habilidades address-normalize

📦

address-normalize

Name: address-normalize
Author: tahodev

Revisión del contenido r1 Riesgo bajo 🌐 Acceso a red📁 Acceso al sistema de archivos⚙️ Comandos externos

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.

Compatible con: Claude Codex Code(CC)

📊 74 Adecuado

Maintain this Skill? Claim it 📊 74 Adecuado

Instalar con mi Agente

Copia esta solicitud en tu Agente. Incluye la página canónica del Skill y el manifiesto.

Solicitud de agente

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.

Tu Agente debe seguir mostrando su plan y solicitar cualquier confirmación exigida por la política de seguridad.

Recursos legibles por agentes

Usa estos enlaces cuando un agente de IA, crawler o script necesite contexto limpio en vez de leer la página completa.

Detalle Markdown GET /skills/tahodev-address-normalize.md Manifest firmado GET /api/skills/tahodev-address-normalize/manifest Lockfile firmado GET /api/skills/tahodev-address-normalize/lockfile

Pruébalo

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

Resultado esperado:

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.

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

Resultado esperado:

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.

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

Resultado esperado:

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.

Auditoría de seguridad

Riesgo bajo

v1 • 13/10/2026 Abrir el informe versionado

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.

Archivos escaneados

320

Líneas analizadas

Elementos de revisión

Falsos positivos ignorados

Preocupaciones de seguridad confirmadas (1)

Bajo

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.

Elementos de revisión de capacidades (3)

Estas son capacidades locales reales que pueden esperarse para esta habilidad, por lo que requieren revisión, pero no se cuentan como comportamiento malicioso confirmado.

Medio

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.

Medio

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.

Medio

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.

Factores de riesgo

Auditado por: codex

Compartir y citar este informe

Comparte el informe de evaluación versionado, la insignia neutral, la tarjeta insertable y las citas. Skillstore presenta evidencias sin decidir si este Skill es seguro.

Abrir el informe versionado

Copiar enlace del informe

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

Insignia Markdown

[![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)

Insignia HTML

<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>

Tarjeta para insertar

<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>

Citas académicas (APA · BibTeX · CFF)

Cita APA

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

Cita BibTeX

@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"

Puntuación de Skillstore

Por qué esta puntuación Confianza de la evidencia: Medio

Arquitectura

Mantenibilidad

Contenido

Comunidad

Cumplimiento de la especificación

Lo que puedes crear

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.

Prueba estos prompts

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.

Mejores prácticas

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.

Evitar

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.

Preguntas frecuentes

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.