스킬 vertical-industry-data-team

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vertical-industry-data-team

Name: vertical-industry-data-team
Author: 图灵数盟

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

Assess Industry Data Assetization Paths

Regulated data projects often fail when generic assetization methods overlook industry rules. This skill structures compliance-first assessments for carbon, seed, energy, and public data.

지원: Claude Codex Code(CC)

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에이전트 요청

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

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Markdown 상세 GET /skills/dhturing-vertical-industry-data-team.md 서명된 manifest GET /api/skills/dhturing-vertical-industry-data-team/manifest 서명된 lockfile GET /api/skills/dhturing-vertical-industry-data-team/lockfile

테스트해 보기

"vertical-industry-data-team" 사용 중입니다. Can charging-network usage data support an assetization project?

예상 결과:

Conditional feasibility. First classify personal, operational, and grid-related data. Confirm de-identification, CII exposure, ownership, auditability, and measurable revenue before selecting a structure.

"vertical-industry-data-team" 사용 중입니다. How should a city plan a five-year public-data authorization?

예상 결과:

Use the five-step authorization process and document scope, operator selection, security duties, product boundaries, and revenue allocation. Track the shorter registration renewal separately.

"vertical-industry-data-team" 사용 중입니다. Can verified emissions reductions be marketed as official carbon credits?

예상 결과:

Not automatically. Verify the approved methodology, MRV evidence, validation path, crediting period, registration status, and issuance estimate. Keep commercial carbon claims distinct from official CCER.

보안 감사

안전

v1 • 2026. 9. 27. 버전별 보고서 열기

All twelve static findings are false positives caused by documentation examples, Markdown formatting, public website links, and UTF-8 Chinese prose. No executable payload, hidden file operation, unauthorized network request, prompt injection, or data-exfiltration intent was found.

스캔된 파일

275

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검토 항목

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위험 요인

📁 파일 시스템 접근 (2)

profile.md:38 profile.md:38

⚙️ 외부 명령어 (2)

SKILL.md:20 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

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버전별 보고서 열기

보고서 링크 복사

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

HTML 배지

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

임베드 카드

<iframe src="https://skillstore.io/embed/skills/dhturing-vertical-industry-data-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). vertical-industry-data-team security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-vertical-industry-data-team/audits/1

BibTeX 인용

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

Skillstore 점수

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사양 준수

만들 수 있는 것

Screen a Carbon Data Project

Assess MRV readiness, CCER boundaries, evidence gaps, and possible assetization paths before commissioning specialist work.

Evaluate Energy Data Commercialization

Classify storage or charging data, identify CII and important-data concerns, and test whether cash flows are measurable.

Plan Public Data Authorization

Structure the authorization process, required deliverables, term controls, operating boundaries, and renewal reminders for a regional project.

이 프롬프트를 사용해 보세요

Identify the Industry Gates

Review this [industry] data project. List its data types, main compliance gates, missing evidence, and the next three actions.

Compare Assetization Routes

Compare accounting recognition, data licensing, authorized operation, and structured revenue rights for [project]. Explain eligibility, blockers, evidence, and tradeoffs.

Build a Cross-Role Delivery Plan

Create a phased delivery plan for [project]. Assign specialist responsibilities, required inputs, deliverables, quality checks, decision gates, and escalation points.

Challenge an Investment Proposal

Stress-test this [industry] data investment proposal. Separate verified facts from assumptions, test regulatory claims, assess measurable cash flows, and recommend proceed, pause, or reject.

모범 사례

Provide the jurisdiction, project stage, data inventory, participants, intended buyers, and available evidence.
Confirm current policies with official sources before relying on dates, limits, or approval requirements.
Keep regulatory rights, data rights, intellectual property, and revenue rights separate throughout the assessment.

피하기

Do not treat a generic data assetization process as sufficient for a regulated industry.
Do not present commercial tokens, revenue rights, or private certificates as official regulatory instruments.
Do not infer ownership, approval, or financial value when supporting evidence is missing.

자주 묻는 질문

Which industries does this skill cover?

It covers carbon, seed, power and energy storage, and public data authorization scenarios.

Does it provide legal or regulatory approval?

No. It organizes issues and evidence but does not replace qualified advisers or competent authorities.

Can it calculate a final data asset valuation?

No. It can identify valuation inputs and cash-flow questions, but specialists must validate assumptions and issue formal opinions.

What information should I provide?

Provide the jurisdiction, data inventory, participants, project stage, proposed transaction, available approvals, and supporting evidence.

Can it compare several industries?

Yes. It can compare compliance gates, ownership complexity, buyers, commercialization routes, and required deliverables across the four covered sectors.

How current is the regulatory guidance?

The source states a review date of September 23, 2026. Verify every policy and deadline against current official publications.