Навыки data-ip-expert
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data-ip-expert

Ревизия содержимого r1 Безопасно 📁 Доступ к файловой системе⚙️ Внешние команды🌐 Доступ к сети

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.

Поддерживает: Claude Codex Code(CC)
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Запрос агента
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.

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 «data-ip-expert». Should an internal customer-scoring model use patent or trade secret protection?

Ожидаемый результат:

  • 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.

Использование «data-ip-expert». Create a preservation plan for a dataset that changes monthly.

Ожидаемый результат:

  • 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.

Использование «data-ip-expert». What should we prepare before a data IP registration consultation?

Ожидаемый результат:

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

Аудит безопасности

Безопасно

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.

4
Просканировано файлов
432
Проанализировано строк
0
Пункты проверки
0
Ложные срабатывания проигнорированы

Факторы риска

📁 Доступ к файловой системе (2)
⚙️ Внешние команды (3)
🌐 Доступ к сети (2)
Последний завершенный статический и семантический аудит не обнаружил подтвержденных проблем безопасности. Это не доказывает отсутствие побочных эффектов у навыка.
Аудитор:: codex
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Оценка безопасности

Копировать ссылку на отчёт

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

Значок Markdown

[![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)

Значок HTML

<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>

Встраиваемая карточка

<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>
Академические ссылки (APA · BibTeX · CFF)

Цитата APA

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

Цитата BibTeX

@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"

Оценка Skillstore

Почему такая оценка Достоверность доказательств: Средний
55
Архитектура
85
Сопровождаемость
87
Контент
65
Сообщество
83
Соответствие спецификации

Что вы можете построить

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.

Попробуйте эти промпты

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.

Лучшие практики

  • 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.

Избегать

  • 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.

Часто задаваемые вопросы

Can raw data receive patent protection?
Raw data generally cannot. A technically implemented processing method, model, or system may warrant patent assessment.
Does blockchain preservation prove ownership?
No. It can support existence and integrity at a time, but ownership and lawful origin need separate evidence.
Can copyright protect a database?
It may protect an original selection or arrangement. It usually does not protect factual data by itself.
When is trade secret protection suitable?
It suits valuable nonpublic information when the owner applies reasonable, documented confidentiality measures.
Does the skill submit applications?
No. It prepares analysis and checklists for review by authorities, lawyers, or patent professionals.
Which jurisdiction does the guidance cover?
The knowledge base focuses on China. Confirm current national and regional requirements before taking action.

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

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