技能 address-normalize

📦

address-normalize

Name: address-normalize
Author: tahodev

內容修訂 r1 低風險 🌐 網路存取📁 檔案系統存取⚙️ 外部命令

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.

支援: Claude Codex Code(CC)

📊 74 尚可

Maintain this Skill? Claim it 📊 74 尚可

使用我的智慧代理安裝

將此請求複製給你的智慧代理，其中包含權威 Skill 頁面和清單。

智能體請求

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.

你的智慧代理仍應顯示其計畫，並依安全政策請求必要確認。

Agent 可讀資源

當 AI Agent、爬蟲或腳本需要乾淨脈絡、而不是讀取完整頁面時，請使用這些連結。

Markdown 詳情 GET /skills/tahodev-address-normalize.md 已簽名 manifest GET /api/skills/tahodev-address-normalize/manifest 已簽名 lockfile GET /api/skills/tahodev-address-normalize/lockfile

測試它

正在使用「address-normalize」。 Normalize 東京都千代田区内幸町1丁目1-1.

預期結果:

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.

正在使用「address-normalize」。 Normalize 新宿区歌舞伎町一丁目4-1.

預期結果:

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.

正在使用「address-normalize」。 Normalize 東京都千代田区内幸町 without a chome.

預期結果:

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.

安全審計

低風險

v1 • 2026/10/13 開啟版本化報告

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.

已掃描檔案

320

分析行數

複核項目

已忽略的誤報

已確認的安全問題 (1)

低

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.

能力複核項目 (3)

這些是真實的本機能力，對此技能而言可能是預期行為，因此需要複核，但不會按已確認的惡意行為計分。

中

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.

中

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.

中

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.

審計單位: codex

分享與引用此報告

分享版本化評估報告、中性徽章、嵌入卡片與引用。Skillstore 只報告證據，不判斷該 Skill 是否安全。

開啟版本化報告

複製報告連結

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

Markdown 徽章

[![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 徽章

<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>

嵌入卡片

<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>

學術引用 (APA · BibTeX · CFF)

APA 引用

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

BibTeX 引用

@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 評分

評分依據證據置信度: 中

架構

可維護性

內容

社群

規範符合度

你可以打造什麼

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.

試試這些提示

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.

最佳實務

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.

避免

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.

常見問題

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.