技能 data-element-market-expert

📦

data-element-market-expert

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

內容修訂 r1 安全 📁 檔案系統存取⚙️ 外部命令🌐 網路存取

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.

支援: Claude Codex Code(CC)

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智能體請求

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.

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Agent 可讀資源

當 AI Agent、爬蟲或腳本需要乾淨脈絡、而不是讀取完整頁面時，請使用這些連結。

Markdown 詳情 GET /skills/dhturing-data-element-market-expert.md 已簽名 manifest GET /api/skills/dhturing-data-element-market-expert/manifest 已簽名 lockfile GET /api/skills/dhturing-data-element-market-expert/lockfile

測試它

正在使用「data-element-market-expert」。 Assess the current maturity of China's data element market.

預期結果:

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.

正在使用「data-element-market-expert」。 Evaluate whether a data asset service model is proven.

預期結果:

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.

正在使用「data-element-market-expert」。 Create a market sizing approach for a regional data compliance service.

預期結果:

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.

安全審計

安全

v1 • 2026/9/27 開啟版本化報告

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.

已掃描檔案

443

分析行數

複核項目

已忽略的誤報

風險因素

📁 檔案系統存取 (2)

profile.md:38 profile.md:38

⚙️ 外部命令 (3)

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

🌐 網路存取 (2)

SKILL.md:6 SKILL.md:12

最近一次完成的靜態與語意稽核未偵測到已確認的安全發現。這並不能證明該 Skill 沒有副作用。

審計單位: codex

分享與引用此報告

分享版本化評估報告、中性徽章、嵌入卡片與引用。Skillstore 只報告證據，不判斷該 Skill 是否安全。

開啟版本化報告

複製報告連結

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

Markdown 徽章

[![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 徽章

<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>

嵌入卡片

<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>

學術引用 (APA · BibTeX · CFF)

APA 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 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 評分

評分依據證據置信度: 中

架構

可維護性

內容

社群

規範符合度

你可以打造什麼

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.

試試這些提示

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.

最佳實務

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.

避免

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.

常見問題

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.