Skills data-element-market-expert

📦

data-element-market-expert

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

Content revision r1 Safe 📁 Filesystem access⚙️ External commands🌐 Network access

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.

Supports: Claude Codex Code(CC)

🥉 77 Bronze

Install with my Agent

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Agent request

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.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/dhturing-data-element-market-expert.md Signed manifest GET /api/skills/dhturing-data-element-market-expert/manifest Signed lockfile GET /api/skills/dhturing-data-element-market-expert/lockfile

Test it

Using "data-element-market-expert". Assess the current maturity of China's data element market.

Expected outcome:

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.

Using "data-element-market-expert". Evaluate whether a data asset service model is proven.

Expected outcome:

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.

Using "data-element-market-expert". Create a market sizing approach for a regional data compliance service.

Expected outcome:

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.

Security Audit

Safe

v1 • 9/27/2026 Open versioned report

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.

Files scanned

443

Lines analyzed

Review items

False positives ignored

Risk Factors

📁 Filesystem access (2)

profile.md:38 profile.md:38

⚙️ External commands (3)

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

🌐 Network access (2)

SKILL.md:6 SKILL.md:12

No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.

Audited by: codex

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Academic citations (APA · BibTeX · CFF)

APA citation

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 citation

@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 Score

Why this score Evidence Confidence: Medium

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

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.

Try These Prompts

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.

Best Practices

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.

Avoid

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.

Frequently Asked Questions

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.