スキル data-asset-capitalization-team

📦

data-asset-capitalization-team

Name: data-asset-capitalization-team
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

Plan Auditable Data Asset Capitalization

Organizations often lack a coordinated process for recognizing data resources as assets. This skill structures evidence, roles, controls, deliverables, and review gates.

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-asset-capitalization-team" from https://skillstore.io/skills/dhturing-data-asset-capitalization-team.md and its manifest at https://skillstore.io/api/skills/dhturing-data-asset-capitalization-team/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-asset-capitalization-team.md 署名済み manifest GET /api/skills/dhturing-data-asset-capitalization-team/manifest 署名済み lockfile GET /api/skills/dhturing-data-asset-capitalization-team/lockfile

テストする

「data-asset-capitalization-team」を使用しています。 Assess whether our customer analytics dataset is ready for capitalization.

期待される結果:

Decision: remediation required before recognition.
Evidence gaps: usage rights, personal information controls, development-stage approvals, and labor records.
Next review: compliance and ownership evidence must pass before valuation work begins.

「data-asset-capitalization-team」を使用しています。 Create a project plan for one data product.

期待される結果:

Phase 1: confirm scope, ownership, legal source, and recognition criteria.
Phase 2: complete inventory, governance, quality testing, cost attribution, and valuation support.
Phase 3: prepare accounting treatment, disclosure, ledger records, and audit evidence.

「data-asset-capitalization-team」を使用しています。 What should an audit-ready delivery package contain?

期待される結果:

The package includes source evidence, ownership records, data inventory, quality results, cost schedules, valuation support, accounting conclusions, disclosures, and ledger controls.

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 static findings are false positives caused by documentation paths, Markdown backticks, ordinary website links, or entropy heuristics on Chinese text. No executable code, network request, obfuscated payload, prompt injection, or harmful intent was found.

スキャンされたファイル

254

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:31

🌐 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-asset-capitalization-team/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-asset-capitalization-team/security.svg)](https://skillstore.io/skills/dhturing-data-asset-capitalization-team?utm_source=security_passport_badge)

HTMLバッジ

<a href="https://skillstore.io/skills/dhturing-data-asset-capitalization-team?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-data-asset-capitalization-team/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-asset-capitalization-team.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-asset-capitalization-team security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-asset-capitalization-team/audits/1

BibTeX形式の引用

@techreport{dhturing-data-asset-capitalization-team-2026,
  author = {图灵数盟},
  title = {data-asset-capitalization-team security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/dhturing-data-asset-capitalization-team/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-asset-capitalization-team 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-asset-capitalization-team/audits/1"
identifiers:
  - type: other
    value: "skillstore:dhturing-data-asset-capitalization-team: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

Assess capitalization readiness

Create an evidence checklist, risk register, and first-wave resource shortlist for a data owner.

Prepare an accounting workstream

Map research and development stages, cost evidence, recognition criteria, disclosures, and audit review points.

Coordinate specialist delivery

Assign responsibilities, dependencies, acceptance criteria, and deliverables across a multidisciplinary project.

これらのプロンプトを試す

Start a readiness review

Assess capitalization readiness for [data resource]. List required evidence, major risks, responsible roles, and immediate next steps.

Build a delivery plan

Create a phased capitalization plan for [organization]. Include owners, dependencies, deliverables, review gates, and estimated timing.

Design an audit package

Design an audit-ready evidence package for [data resource]. Cover ownership, compliance, quality, costs, valuation, accounting treatment, disclosure, and ledger controls.

Challenge a capitalization case

Review this capitalization case: [case details]. Test assumptions, identify evidence gaps, assign specialists, and recommend proceed, remediate, or stop decisions.

ベストプラクティス

Confirm legal source and ownership before cost attribution, valuation, or accounting design.
Link every conclusion to dated evidence, an accountable owner, and a review status.
Validate accounting, legal, valuation, and audit conclusions with qualified professionals.

回避

Do not treat estimated value as automatic evidence for accounting recognition.
Do not inflate costs or valuation assumptions to reach a target asset amount.
Do not continue when ownership, personal information, or source legality remains unresolved.

よくある質問

Does this skill decide whether data can be recognized as an asset?

It structures the assessment and evidence. Qualified professionals must approve the final accounting treatment.

Can it value a data asset?

It can organize methods, assumptions, and evidence. A qualified valuer should issue any formal valuation opinion.

Does it process the underlying dataset?

No. It plans governance and assessment work without automatically accessing or copying source data.

Which project stages are covered?

It covers initiation, readiness, compliance, governance, quality, valuation, cost attribution, accounting, disclosure, ledger management, and audit support.

Can it support an existing project?

Yes. Provide the current stage, available evidence, unresolved issues, roles, and required decision.

Are the cited policies always current?

No. Verify every policy, standard, date, and jurisdiction before relying on it.