技能 data-value-assessment-expert

📦

data-value-assessment-expert

Name: data-value-assessment-expert
Author: 图灵数盟

内容修订 r1 安全 📁 文件系统访问⚙️ 外部命令🌐 网络访问

Assess Data Value and Prioritize Opportunities

Organizations often overlook valuable uses for their data or cannot explain where value originates. This skill provides structured diagnosis, measurement guidance, and prioritized improvement actions.

支持: Claude Codex Code(CC)

🥉 77 青铜

使用我的智能体安装

将此请求复制给你的智能体，其中包含权威 Skill 页面和清单。

智能体请求

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

你的智能体仍应展示其计划，并按安全策略请求必要确认。

Agent 可读资源

当 AI Agent、爬虫或脚本需要干净上下文，而不是读取完整页面时，请使用这些链接。

Markdown 详情 GET /skills/dhturing-data-value-assessment-expert.md 已签名 manifest GET /api/skills/dhturing-data-value-assessment-expert/manifest 已签名 lockfile GET /api/skills/dhturing-data-value-assessment-expert/lockfile

测试它

正在使用“data-value-assessment-expert”。 Assess customer service transcripts for overlooked value.

预期结果:

Strongest value: cost reduction through automated issue classification.
Secondary value: product improvement from recurring complaint patterns.
Main gap: unclear consent for uses beyond service delivery.
Next action: validate permissions before testing external scenarios.

正在使用“data-value-assessment-expert”。 Diagnose the value of weekly logistics data.

预期结果:

The weakest factor is buyer action because interest lacks paid validation. Run two buyer interviews and a limited pilot before forecasting revenue.

正在使用“data-value-assessment-expert”。 Prioritize three uses for equipment sensor data.

预期结果:

First: predictive maintenance, supported by downtime records and an internal owner.
Second: warranty risk analysis, pending quality checks.
Third: external benchmarking, pending authorization and buyer validation.

安全审计

安全

v1 • 2026/9/27 打开版本化报告

All twelve static findings are false positives. The files contain normal Markdown documentation, Chinese UTF-8 prose, installation paths, inline code formatting, and author links without executable behavior, concealed payloads, or prompt injection.

已扫描文件

424

分析行数

复核项

已忽略误报

风险因素

📁 文件系统访问 (2)

profile.md:38 profile.md:38

⚙️ 外部命令 (3)

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

🌐 网络访问 (2)

SKILL.md:6 SKILL.md:12

最新一次完成的静态与语义审计未检测到已确认的安全发现。这并不能证明该 Skill 没有副作用。

审计者: codex

分享与引用此报告

分享版本化评估报告、中性徽章、嵌入卡片和引用。Skillstore 只报告证据，不判断该 Skill 是否安全。

打开版本化报告

复制报告链接

https://skillstore.io/skills/dhturing-data-value-assessment-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-value-assessment-expert/security.svg)](https://skillstore.io/skills/dhturing-data-value-assessment-expert?utm_source=security_passport_badge)

HTML 徽章

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

嵌入卡片

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

学术引用 (APA · BibTeX · CFF)

APA 引用

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

BibTeX 引用

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

Skillstore 评分

评分依据证据置信度: 中

架构

可维护性

内容

社区

规范符合性

你能构建什么

Map overlooked value

Review a data portfolio across nine value types and identify evidence gaps.

Prioritize product scenarios

Compare candidate data products and rank their most credible use scenarios.

Prepare investment decisions

Separate realized benefits from potential value and identify improvement priorities.

试试这些提示

Identify value types

Review this dataset across all nine value types. For each type, state relevance, evidence, and missing information.

Diagnose value factors

Score the five value factors from one to five. Explain each score, identify the weakest factor, and recommend improvements.

Rank value scenarios

Compare these internal and external scenarios by market scale, buyer value, competition, compliance, and evidence. Rank them with stated assumptions.

Build an assessment report

Create a complete data value assessment. Include value types, five-factor diagnosis, data map, scenario ranking, measurement ranges, decay risks, and actions.

最佳实践

Provide evidence for each score and label every assumption.
Separate realized benefits, validated opportunities, and speculative potential.
Complete rights and compliance checks before recommending external use.

避免

Do not treat stated buyer interest as proven willingness to pay.
Do not present potential value as current revenue or asset value.
Do not rank scenarios without considering permissions, quality, and alternatives.

常见问题

Does this skill produce a formal asset valuation?

No. It analyzes value sources and opportunities but does not replace a licensed valuation report.

What information should I provide?

Provide data sources, fields, quality, permissions, current uses, candidate buyers, operating costs, and available performance evidence.

How are value opportunities classified?

The framework reviews nine types, including revenue, savings, efficiency, risk, decisions, financing, ecosystem, compliance, and strategic options.

Can it estimate monetary value?

It can create evidence-based ranges when sufficient inputs exist. Every estimate should state its method, assumptions, and uncertainty.

How does it find cross-industry opportunities?

It examines other industries, buyer problems, comparable uses, and complementary datasets. These opportunities still require market and compliance validation.

Can it handle confidential data?

Use summaries or approved samples. Follow organizational controls and avoid sharing personal, restricted, or proprietary records without authorization.