스킬 data-asset-capitalization-team

📦

data-asset-capitalization-team

Name: data-asset-capitalization-team
Author: 图灵数盟

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

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.

지원: Claude Codex Code(CC)

🥉 77 브론즈

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내 에이전트로 설치

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에이전트 요청

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.

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

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Markdown 상세 GET /skills/dhturing-data-asset-capitalization-team.md 서명된 manifest GET /api/skills/dhturing-data-asset-capitalization-team/manifest 서명된 lockfile GET /api/skills/dhturing-data-asset-capitalization-team/lockfile

테스트해 보기

"data-asset-capitalization-team" 사용 중입니다. Assess whether our customer analytics dataset is ready for capitalization.

예상 결과:

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" 사용 중입니다. Create a project plan for one data product.

예상 결과:

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" 사용 중입니다. What should an audit-ready delivery package contain?

예상 결과:

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

보안 감사

안전

v1 • 2026. 9. 27. 버전별 보고서 열기

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.

스캔된 파일

254

분석된 줄 수

검토 항목

오탐 무시됨

위험 요인

📁 파일 시스템 접근 (2)

profile.md:38 profile.md:38

⚙️ 외부 명령어 (3)

SKILL.md:20 SKILL.md:26 SKILL.md:31

🌐 네트워크 접근 (2)

SKILL.md:6 SKILL.md:12

가장 최근에 완료된 정적·의미론적 감사에서 확인된 보안 발견 사항이 감지되지 않았습니다. 이는 스킬에 부작용이 없음을 증명하지 않습니다.

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/dhturing-data-asset-capitalization-team/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![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 배지

<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>

임베드 카드

<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>

학술 인용 (APA · BibTeX · CFF)

APA 인용

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 인용

@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 점수

이 점수의 이유 증거 신뢰도: 중간

아키텍처

유지보수성

콘텐츠

커뮤니티

사양 준수

만들 수 있는 것

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.

이 프롬프트를 사용해 보세요

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.

모범 사례

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.

피하기

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.

자주 묻는 질문

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.