Habilidades vertical-industry-data-expert

📦

vertical-industry-data-expert

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

Revisão do conteúdo r1 Seguro 📁 Acesso ao sistema de arquivos⚙️ Comandos externos🌐 Acesso à rede

Plan Industry-Specific Data Asset Strategies

Generic data asset plans can miss sector rules, data ownership, buyer needs, and approval steps. This skill organizes industry selection, data assessment, compliance screening, commercialization scenarios, and repeatable delivery plans.

Suporta: Claude Codex Code(CC)

🥉 77 Bronze

Instalar com meu Agente

Copie esta solicitação para o seu Agente. Ela inclui a página canônica do Skill e o manifesto.

Solicitação do agente

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

Seu Agente ainda deve apresentar o plano e solicitar qualquer confirmação exigida pela política de segurança.

Recursos legíveis por agentes

Use estes links quando um agente de IA, crawler ou script precisar de contexto limpo em vez de ler a página completa.

Detalhe em Markdown GET /skills/dhturing-vertical-industry-data-expert.md manifest assinado GET /api/skills/dhturing-vertical-industry-data-expert/manifest lockfile assinado GET /api/skills/dhturing-vertical-industry-data-expert/lockfile

Testar

Usando "vertical-industry-data-expert". Assess whether a hospital imaging dataset is ready for commercialization.

Resultado esperado:

Readiness: conditional, pending ownership, patient authorization, de-identification, and sector approval review.
Priority evidence: data inventory, notices, consent records, rights agreements, security controls, and permitted-use records.
Next step: obtain specialist review before selecting a buyer or valuation approach.

Usando "vertical-industry-data-expert". Turn a charging-network data project into a replication plan.

Resultado esperado:

Standardize the data inventory, metrics, compliance checks, buyer profile, and acceptance criteria.
Separate reusable methods from client-specific contracts, infrastructure, permissions, and financial assumptions.
Validate the package with a second customer before wider rollout.

Auditoria de segurança

Seguro

v1 • 27/09/2026 Abrir o relatório versionado

All 12 static findings are false positives. The flagged paths, backticks, and URLs are documentation syntax or passive metadata, while the entropy alerts reflect readable multilingual Markdown. No prompt injection, data-exfiltration intent, or executable behavior was found.

Arquivos analisados

505

Linhas analisadas

Itens de revisão

Falsos positivos ignorados

Fatores de risco

📁 Acesso ao sistema de arquivos (2)

profile.md:38 profile.md:38

⚙️ Comandos externos (3)

SKILL.md:20 SKILL.md:26 SKILL.md:33

🌐 Acesso à rede (2)

SKILL.md:6 SKILL.md:12

A auditoria estática e semântica concluída mais recente não detectou achados de segurança confirmados. Isso não comprova que a skill não tenha efeitos colaterais.

Auditado por: claude

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Abrir o relatório versionado

Copiar link do relatório

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

Badge Markdown

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Cartão incorporável

<iframe src="https://skillstore.io/embed/skills/dhturing-vertical-industry-data-expert.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

Citações acadêmicas (APA · BibTeX · CFF)

Citação APA

图灵数盟. (2026). vertical-industry-data-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-vertical-industry-data-expert/audits/1

Citação BibTeX

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

Pontuação do Skillstore

Por que esta pontuação Confiança das evidências: Médio

Arquitetura

Manutenibilidade

Conteúdo

Comunidade

Conformidade com a especificação

O que você pode criar

Prioritize a Data-Rich Sector

Compare candidate industries and select one or two sectors for focused data asset development.

Screen a Sector Data Project

Identify data traits, ownership questions, sensitive data, regulations, approvals, and evidence gaps before design.

Replicate a Benchmark Project

Turn one delivery into reusable materials, validation criteria, buyer messaging, and a rollout sequence.

Teste estes prompts

Describe an Industry Data Opportunity

Analyze the data opportunity in [industry]. List data types, producers, update frequency, quality concerns, and value scenarios. State your assumptions.

Create a Compliance Screening Checklist

Review this [industry] data project in [jurisdiction]. Identify sensitive data, ownership questions, sector rules, approvals, evidence gaps, and required specialist reviews.

Map Scenarios and Buyers

For [data assets], rank commercial scenarios by value and feasibility. For each scenario, describe buyers, budget owners, decision makers, procurement routes, and proof requirements.

Design a Benchmark and Replication Plan

Design a benchmark project for [industry and client]. Include phases, inputs, controls, deliverables, acceptance criteria, dependencies, risks, and a replication plan.

Boas práticas

Provide the industry, jurisdiction, data sources, rights, intended use, and available evidence.
Treat compliance and ownership as decision gates before valuation or commercialization.
Validate recommendations with current regulations, primary evidence, and qualified sector specialists.

Evitar

Do not reuse one generic data asset plan across industries with different regulatory obligations.
Do not present scenario assumptions, estimated values, or cited internal cases as verified facts.
Do not start commercialization while ownership, consent, approval, or data-quality questions remain unresolved.

Perguntas frequentes

Which industries does this skill cover?

It provides guidance for healthcare, agriculture, energy, education, carbon, trade finance, commodities, entertainment, consumer data, and related sectors.

Can it choose the best industry for my organization?

It can structure and score the decision. Final selection needs verified resources, market evidence, budgets, competition, and organizational priorities.

Does it provide legal or regulatory approval?

No. It identifies review areas and evidence gaps. Qualified specialists and authorities must confirm requirements.

Can it value a dataset?

It can prepare industry context and value scenarios. Defensible valuation requires verified financial evidence, suitable methods, and qualified professionals.

Does the package include the cited internal cases?

No. The knowledge base refers to internal materials, but the underlying documents and datasets are not included.

What information produces the best result?

Provide the industry, jurisdiction, data inventory, ownership evidence, collection basis, intended uses, buyer hypotheses, and known regulatory constraints.