スキル data-element-market-expert

📦

data-element-market-expert

Name: data-element-market-expert
Author: 图灵数盟

コンテンツリビジョン r1 安全 📁 ファイルシステムへのアクセス⚙️ 外部コマンド🌐 ネットワークアクセス

Analyze China's Data Element Market

Data element strategies often rely on fragmented evidence and inflated market claims. This skill structures maturity, competition, opportunities, and sizing with explicit assumptions.

対応: Claude Codex Code(CC)

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自分のエージェントでインストール

このリクエストをエージェントにコピーしてください。正規の Skill ページとマニフェストが含まれています。

エージェントリクエスト

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

エージェントは引き続き計画を提示し、セキュリティポリシーで必要な確認を求める必要があります。

エージェントが読めるリソース

AI エージェント、クローラー、スクリプトがページ全体ではなく整理されたコンテキストを必要とする場合は、これらのリンクを使ってください。

Markdown詳細 GET /skills/dhturing-data-element-market-expert.md 署名済み manifest GET /api/skills/dhturing-data-element-market-expert/manifest 署名済み lockfile GET /api/skills/dhturing-data-element-market-expert/lockfile

テストする

「data-element-market-expert」を使用しています。 Assess the current maturity of China's data element market.

期待される結果:

Stage: transition from model exploration toward scaling.
Signals: established accounting cases, limited transaction volume, early financialization, and emerging public data authorization.
Uncertainty: validate current volumes and policy implementation with dated public sources.

「data-element-market-expert」を使用しています。 Evaluate whether a data asset service model is proven.

期待される結果:

Repeat demand: insufficient evidence until renewal or repeat purchase data is available.
Economics: calculate gross margin after delivery labor, compliance, technology, and partner costs.
Replicability: test delivery effort and conversion across customers or industries.

「data-element-market-expert」を使用しています。 Create a market sizing approach for a regional data compliance service.

期待される結果:

Top-down: narrow total enterprise spending by region, regulated sectors, and addressable service scope.
Bottom-up: multiply qualified customers by annual contract value and realistic penetration.
Cross-check definitions, remove overlapping revenue, and show sensitivity for adoption and pricing.

セキュリティ監査

安全

v1 • 2026/9/27 バージョン別レポートを開く

All static findings are false positives caused by documentation syntax, installation examples, public links, Chinese text, or line-ending encoding. No executable behavior, obfuscation, or prompt injection was found.

スキャンされたファイル

443

解析済み行数

レビュー項目

誤検知を無視

リスク要因

📁 ファイルシステムへのアクセス (2)

profile.md:38 profile.md:38

⚙️ 外部コマンド (3)

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

🌐 ネットワークアクセス (2)

SKILL.md:6 SKILL.md:12

最新の完了済み静的・セマンティック監査では、確認済みのセキュリティ検出事項は見つかりませんでした。これは、スキルに副作用がないことを証明するものではありません。

監査者: codex

このレポートを共有・引用

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バージョン別レポートを開く

レポートリンクをコピー

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

Markdownバッジ

[![Skillstore security assessment](https://skillstore.io/badges/skills/dhturing-data-element-market-expert/security.svg)](https://skillstore.io/skills/dhturing-data-element-market-expert?utm_source=security_passport_badge)

HTMLバッジ

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

埋め込みカード

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

学術引用 (APA · BibTeX · CFF)

APA形式の引用

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

BibTeX形式の引用

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

Skillstore スコア

このスコアの理由証拠の信頼度: 中

アーキテクチャ

保守性

コンテンツ

コミュニティ

仕様準拠

作成できるもの

Prioritize Growth Opportunities

Rank service, industry, circulation, and financialization opportunities against capabilities, timing, evidence, and execution barriers.

Validate a Business Model

Test a proposed data service using repeat demand, positive gross margin, replicability, and documented evidence gaps.

Build a Market Brief

Convert policies, public transactions, company disclosures, and cases into a sourced maturity and competitive landscape briefing.

これらのプロンプトを試す

Map the Market

Explain the data element market layers and identify one opportunity in each layer for [industry]. State assumptions and evidence needs.

Test a Business Model

Assess [business model] using repeat customers, positive gross margin, and replicability. State evidence gaps and propose a validation plan.

Compare Competitors

Compare [competitors] by positioning, customers, pricing, strengths, and risks. Separate verified facts from assumptions and date every source.

Size a Strategic Opportunity

Estimate TAM, SAM, and SOM for [segment] using two methods. Reconcile differences, document assumptions, and provide sensitivity ranges.

ベストプラクティス

Date every source and distinguish primary evidence, secondary research, and assumptions.
Cross-check market size with top-down and bottom-up methods using consistent definitions.
Separate policy intent from observed transactions, repeat demand, positive margins, and replicable delivery.

回避

Do not treat policy support, listings, or pilot announcements as proof of commercial demand.
Do not present precise market numbers without scope, date, method, assumptions, and uncertainty.
Do not generalize from successful cases while ignoring failures, selection bias, or implementation barriers.

よくある質問

Which markets does this skill cover?

It focuses on China's data element market, including resources, products, circulation, services, applications, infrastructure, and emerging financialization.

Can it provide current market data?

It can structure current evidence you provide, but it has no live feed. Verify recent facts with dated public sources.

How does it assess market maturity?

It reviews policy, transactions, financing, technology, adoption, repeat demand, profitability, and replicability against a four-stage framework.

How does it estimate market size?

It combines top-down segmentation with bottom-up customer and contract estimates, then reconciles definitions, overlaps, assumptions, and sensitivity.

Can it compare competitors?

Yes. It compares positioning, offerings, customers, cases, pricing models, strengths, weaknesses, and evidence quality.

Does it replace professional advice?

No. Legal, regulatory, accounting, financing, and investment decisions require qualified professionals and current authoritative sources.