스킬 data-asset-valuation-expert

📦

data-asset-valuation-expert

Name: data-asset-valuation-expert
Author: 图灵数盟

콘텐츠 리비전 r1 안전 📁 파일 시스템 접근⚙️ 외부 명령어🌐 네트워크 접근

Value Data Assets with Evidence

Data assets often lack active markets, making valuation methods and assumptions difficult to defend. This skill structures evidence-based valuations under Chinese appraisal guidance.

지원: Claude Codex Code(CC)

🥉 77 브론즈

Maintain this Skill? Claim it 🥉 77 브론즈

내 에이전트로 설치

이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.

에이전트 요청

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

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

에이전트가 읽기 쉬운 리소스

AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.

Markdown 상세 GET /skills/dhturing-data-asset-valuation-expert.md 서명된 manifest GET /api/skills/dhturing-data-asset-valuation-expert/manifest 서명된 lockfile GET /api/skills/dhturing-data-asset-valuation-expert/lockfile

테스트해 보기

"data-asset-valuation-expert" 사용 중입니다. A retailer wants to value customer behavior data for accounting recognition but has no direct data sales.

예상 결과:

Recommended approach: use the cost method as the primary method and test attributable efficiency gains through the income method. Verify ownership and compliance first.

"data-asset-valuation-expert" 사용 중입니다. A lender asks why financing is lower than the appraised value.

예상 결과:

The appraisal estimates asset value under stated assumptions. Credit limits may apply discounts for liquidity, enforceability, value volatility, and disposal uncertainty.

"data-asset-valuation-expert" 사용 중입니다. Review a valuation using a five-year income period and a high data contribution rate.

예상 결과:

Request evidence for data refresh cycles, customer retention, income attribution, and the contribution benchmark. Test shorter periods and lower contribution rates.

보안 감사

안전

v1 • 2026. 9. 27. 버전별 보고서 열기

All twelve static alerts are false positives caused by Markdown syntax, documented installation paths, public attribution links, and Chinese plaintext entropy. The skill contains no executable code, active network requests, obfuscated payloads, or prompt-injection instructions.

스캔된 파일

428

분석된 줄 수

검토 항목

오탐 무시됨

위험 요인

📁 파일 시스템 접근 (2)

profile.md:38 profile.md:38

⚙️ 외부 명령어 (3)

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

🌐 네트워크 접근 (2)

SKILL.md:6 SKILL.md:12

가장 최근에 완료된 정적·의미론적 감사에서 확인된 보안 발견 사항이 감지되지 않았습니다. 이는 스킬에 부작용이 없음을 증명하지 않습니다.

감사자: codex

이 보고서 공유 및 인용

버전이 지정된 평가 보고서, 중립 배지, 임베드 카드 및 인용을 공유하세요. Skillstore는 근거를 보고하지만 이 Skill의 안전 여부를 판단하지 않습니다.

버전별 보고서 열기

보고서 링크 복사

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

Markdown 배지

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

HTML 배지

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

임베드 카드

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

학술 인용 (APA · BibTeX · CFF)

APA 인용

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

BibTeX 인용

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

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간

아키텍처

유지보수성

콘텐츠

커뮤니티

사양 준수

만들 수 있는 것

Prepare an accounting valuation

Define the asset boundary, select methods, request evidence, and prepare a review-ready valuation analysis.

Assess collateral support

Explain valuation assumptions, financing discounts, report validity, and evidence needed for lender review.

Review appraisal workpapers

Check parameter support, method selection, cross-validation, disclosures, and required signatures before report issuance.

이 프롬프트를 사용해 보세요

Choose a valuation method

Assess this data asset: [description]. Ask for missing facts, then recommend suitable valuation methods and explain the selection.

Build an evidence request

Create a document request for valuing [asset] for [purpose] on [date]. Cover ownership, costs, income, quality, markets, and compliance.

Analyze valuation parameters

Evaluate these assumptions: [assumptions]. Test income attribution, useful life, discount rate, replacement cost, adjustment factors, and comparable transactions.

Draft a cross-validated conclusion

Compare these valuation results: [results]. Reconcile differences, perform sensitivity analysis, state limitations, and draft a defensible conclusion for [audience].

모범 사례

Define the valuation purpose, asset boundary, value type, and date before selecting a method.
Document every material assumption with traceable evidence and run sensitivity tests for uncertain parameters.
Use at least two approaches when feasible and explain differences before forming a conclusion.

피하기

Do not target a desired value or adjust unsupported parameters to meet financing expectations.
Do not treat replacement cost as value without evaluating quality, utility, market demand, and legal constraints.
Do not present an AI-generated analysis as a signed appraisal report from a licensed institution.

자주 묻는 질문

Which valuation methods does this skill support?

It supports income, cost, and market approaches, including method selection and cross-validation.

Can it produce an official appraisal report?

It can draft report content, but a qualified institution and authorized appraisers must issue any official report.

What information should I provide?

Provide the valuation purpose, asset scope, date, ownership evidence, costs, income forecasts, quality records, contracts, and comparable transactions.

Can data without direct revenue be valued?

Yes. The cost approach may be suitable, while measurable cost savings or efficiency gains may support an income analysis.

Why can financing be lower than appraised value?

Lenders may discount for limited liquidity, uncertain disposal, regulatory risk, enforceability, and value volatility.

Does it work outside China?

The analytical methods are broadly useful, but regulatory references and reporting requirements require local professional review.