スキル data-ip-expert

📦

data-ip-expert

Name: data-ip-expert
Author: 图灵数盟

コンテンツリビジョン r1 安全 📁 ファイルシステムへのアクセス⚙️ 外部コマンド🌐 ネットワークアクセス

Design a Data IP Protection Strategy

Data teams often lack a clear protection path for datasets, algorithms, and processing results. This skill compares legal options and structures evidence-preservation plans.

対応: Claude Codex Code(CC)

🥉 77 ブロンズ

Maintain this Skill? Claim it 🥉 77 ブロンズ

自分のエージェントでインストール

このリクエストをエージェントにコピーしてください。正規の Skill ページとマニフェストが含まれています。

エージェントリクエスト

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

エージェントは引き続き計画を提示し、セキュリティポリシーで必要な確認を求める必要があります。

エージェントが読めるリソース

AI エージェント、クローラー、スクリプトがページ全体ではなく整理されたコンテキストを必要とする場合は、これらのリンクを使ってください。

Markdown詳細 GET /skills/dhturing-data-ip-expert.md 署名済み manifest GET /api/skills/dhturing-data-ip-expert/manifest 署名済み lockfile GET /api/skills/dhturing-data-ip-expert/lockfile

テストする

「data-ip-expert」を使用しています。 Should an internal customer-scoring model use patent or trade secret protection?

期待される結果:

Primary path: assess trade secret protection because the model is not intended for disclosure.
Patent review: evaluate whether the model produces a concrete technical effect and meets novelty requirements.
Next evidence: access logs, confidentiality agreements, model versions, development records, and a professional patent search.

「data-ip-expert」を使用しています。 Create a preservation plan for a dataset that changes monthly.

期待される結果:

Create a baseline hash for the approved dataset and retain the original in controlled storage.
Record each monthly version, processing steps, responsible staff, timestamps, and ownership statements.
Use an independent timestamp or suitable preservation service, then test certificate verification and archive recovery.

「data-ip-expert」を使用しています。 What should we prepare before a data IP registration consultation?

期待される結果:

Prepare the dataset description, lawful source records, processing methodology, investment evidence, sample data, ownership agreements, version history, and applicable regional rules.

セキュリティ監査

安全

v1 • 2026/9/27 バージョン別レポートを開く

All 12 static findings are false positives caused by Markdown links, inline code formatting, installation paths, or entropy heuristics on multilingual text. The reviewed files contain guidance only, with no executable commands, network requests, obfuscated payloads, or prompt injection.

スキャンされたファイル

432

解析済み行数

レビュー項目

誤検知を無視

リスク要因

📁 ファイルシステムへのアクセス (2)

profile.md:38 profile.md:38

⚙️ 外部コマンド (3)

SKILL.md:20 SKILL.md:26 SKILL.md:33

🌐 ネットワークアクセス (2)

SKILL.md:6 SKILL.md:12

最新の完了済み静的・セマンティック監査では、確認済みのセキュリティ検出事項は見つかりませんでした。これは、スキルに副作用がないことを証明するものではありません。

監査者: codex

このレポートを共有・引用

バージョン付き評価レポート、中立的なバッジ、埋め込みカード、引用を共有できます。Skillstore は証拠を報告しますが、この Skill が安全かどうかは判断しません。

バージョン別レポートを開く

レポートリンクをコピー

https://skillstore.io/skills/dhturing-data-ip-expert/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdownバッジ

[![Skillstore security assessment](https://skillstore.io/badges/skills/dhturing-data-ip-expert/security.svg)](https://skillstore.io/skills/dhturing-data-ip-expert?utm_source=security_passport_badge)

HTMLバッジ

<a href="https://skillstore.io/skills/dhturing-data-ip-expert?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-data-ip-expert/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

埋め込みカード

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

学術引用 (APA · BibTeX · CFF)

APA形式の引用

图灵数盟. (2026). data-ip-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-ip-expert/audits/1

BibTeX形式の引用

@techreport{dhturing-data-ip-expert-2026,
  author = {图灵数盟},
  title = {data-ip-expert security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/dhturing-data-ip-expert/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: "data-ip-expert security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "图灵数盟"
date-released: "2026-09-27"
url: "https://skillstore.io/skills/dhturing-data-ip-expert/audits/1"
identifiers:
  - type: other
    value: "skillstore:dhturing-data-ip-expert:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore スコア

このスコアの理由証拠の信頼度: 中

アーキテクチャ

保守性

コンテンツ

コミュニティ

仕様準拠

作成できるもの

Protect a New Data Product

Compare protection paths for a dataset, processing workflow, and related reports before launch.

Strengthen Trade Secret Controls

Assess confidentiality measures and create an evidence checklist for sensitive datasets and models.

Prepare Registration Materials

Organize processing evidence, ownership records, and supporting materials for professional review.

これらのプロンプトを試す

Classify My Data Result

Classify this result as a dataset, algorithm, model, report, or visualization: [description]. Explain which facts need clarification.

Compare Protection Paths

Compare copyright, patent, trade secret, and data IP registration for [asset]. Consider disclosure plans, originality, technical features, and jurisdiction.

Design an Evidence Plan

Design an evidence-preservation plan for [asset]. Cover hashes, timestamps, version changes, ownership records, access controls, retention, and independent verification.

Build an Integrated Protection Program

Create a phased protection program for [portfolio]. Include asset inventory, path selection, controls, registrations, contracts, evidence, owners, dependencies, and review gates.

ベストプラクティス

Document data sources, processing contributions, ownership, and authorization before selecting a protection path.
Use layered protection when different components require different legal and technical controls.
Validate current regional rules and obtain professional review before filing or enforcement.

回避

Do not assume a blockchain record proves ownership, legality, or factual accuracy.
Do not claim trade secret protection without documented and consistently enforced confidentiality measures.
Do not disclose potentially patentable details before reviewing novelty and filing strategy.