vertical-industry-data-team
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.
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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.Ваш Агент по-прежнему должен показать план и запросить все подтверждения, требуемые политикой безопасности.
Ресурсы для AI-агентов
Используйте эти ссылки, когда AI-агенту, crawler или script нужен чистый контекст вместо полной страницы.
Протестировать
Использование «vertical-industry-data-team». Can charging-network usage data support an assetization project?
Ожидаемый результат:
Conditional feasibility. First classify personal, operational, and grid-related data. Confirm de-identification, CII exposure, ownership, auditability, and measurable revenue before selecting a structure.
Использование «vertical-industry-data-team». How should a city plan a five-year public-data authorization?
Ожидаемый результат:
Use the five-step authorization process and document scope, operator selection, security duties, product boundaries, and revenue allocation. Track the shorter registration renewal separately.
Использование «vertical-industry-data-team». Can verified emissions reductions be marketed as official carbon credits?
Ожидаемый результат:
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.
Аудит безопасности
БезопасноAll 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.
Факторы риска
📁 Доступ к файловой системе (2)
⚙️ Внешние команды (2)
🌐 Доступ к сети (2)
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Копировать ссылку на отчёт
https://skillstore.io/skills/dhturing-vertical-industry-data-team/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportЗначок Markdown
[](https://skillstore.io/skills/dhturing-vertical-industry-data-team?utm_source=security_passport_badge)Значок HTML
<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>Встраиваемая карточка
<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>Академические ссылки (APA · BibTeX · CFF)
Цитата APA
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/1Цитата BibTeX
@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"
Оценка Skillstore
Почему такая оценка Достоверность доказательств: СреднийЧто вы можете построить
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.
Попробуйте эти промпты
Review this [industry] data project. List its data types, main compliance gates, missing evidence, and the next three actions.
Compare accounting recognition, data licensing, authorized operation, and structured revenue rights for [project]. Explain eligibility, blockers, evidence, and tradeoffs.
Create a phased delivery plan for [project]. Assign specialist responsibilities, required inputs, deliverables, quality checks, decision gates, and escalation points.
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.
Лучшие практики
- 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.
Избегать
- 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.
Часто задаваемые вопросы
Which industries does this skill cover?
Does it provide legal or regulatory approval?
Can it calculate a final data asset valuation?
What information should I provide?
Can it compare several industries?
How current is the regulatory guidance?
Сведения для разработчиков
Автор
图灵数盟Лицензия
MIT
Ревизия Skillstore
r1
Примечание о версии
Автор не указал версию.
Ссылка
50b73f83991cf073cbdf3f5afad2bbac71dd3bae
Актуальность поддержки
30.09.2026
Использование
0 загрузок · 0 просмотров
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