스킬 data-monetization-expert

📦

data-monetization-expert

Name: data-monetization-expert
Author: 图灵数盟

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

Choose Your Fastest Data Monetization Path

Many organizations hold valuable data but struggle to turn it into real revenue. This skill applies a seven-path model, DMS scoring, and three-database framework to pick the shortest route from data to cash.

지원: Claude Codex Code(CC)

🥉 77 브론즈

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내 에이전트로 설치

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에이전트 요청

Review the Skillstore skill "data-monetization-expert" from https://skillstore.io/skills/dhturing-data-monetization-expert.md and its manifest at https://skillstore.io/api/skills/dhturing-data-monetization-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-monetization-expert.md 서명된 manifest GET /api/skills/dhturing-data-monetization-expert/manifest 서명된 lockfile GET /api/skills/dhturing-data-monetization-expert/lockfile

테스트해 보기

"data-monetization-expert" 사용 중입니다. We hold anonymized regional consumer spending data. Score it and tell us the fastest path to revenue.

예상 결과:

The skill returns a DMS score across the five dimensions, a disposition such as act-now, and a ranked shortlist of monetization paths with the recommended primary path and the reasoning for choosing it first.

"data-monetization-expert" 사용 중입니다. Help us design a recurring revenue mix instead of one-off projects.

예상 결과:

The skill outlines a revenue structure that moves recurring income above fifty percent, names the income models to combine, and describes a quarterly review cadence to keep the mix on target.

보안 감사

안전

v1 • 2026. 9. 27. 버전별 보고서 열기

This is a documentation-only Agent Skill written in Chinese that provides a business framework for data monetization (seven-path model, DMS scoring, three databases). All 12 static findings were adjudicated as false positives: the flagged backtick patterns are Markdown inline-code spans referencing documentation files, the hidden-file findings are install-path examples inside a fenced code block, the hardcoded URLs point to the author's own company website, and the high-entropy heuristics fire on ordinary CJK prose. No executable code, network calls, credential access, or prompt-injection content was found in any file.

스캔된 파일

458

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: claude

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

HTML 배지

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

임베드 카드

<iframe src="https://skillstore.io/embed/skills/dhturing-data-monetization-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-monetization-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-monetization-expert/audits/1

BibTeX 인용

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

Rank monetization paths for a data asset

Score a dataset with the DMS model and compare the seven paths to decide which route reaches revenue fastest.

Build a demand database from scratch

Define the fields to collect and the acquisition channels needed to identify who will buy the data.

Shift revenue toward recurring income

Redesign a project-based revenue mix into a structure where recurring revenue exceeds half of total income.

이 프롬프트를 사용해 보세요

Quick monetization potential check

We have a dataset about [describe the data]. Use the DMS model to score its monetization potential and tell me whether to act now, nurture, or defer.

Compare the seven paths

For our [describe] data assets, compare the seven monetization paths and recommend one primary path and one supporting path, with the reasoning for each.

Design a full monetization scheme

Design a complete monetization scheme for selling [data product] to [target buyer], covering what to sell, pricing, delivery, and how revenue is recognized.

Rebalance the revenue structure

Our income is mostly project-based. Design a revenue structure that raises recurring revenue above fifty percent, and outline a quarterly review plan to track progress.

모범 사례

State your data's ownership clarity, quality, and compliance status up front so the DMS scoring is accurate.
Ask for a primary path plus supporting paths, then commit to the fastest route to first revenue before expanding.
Request reference revenue ranges with stated assumptions rather than a single fixed number.

피하기

Do not treat the reference revenue ranges as guaranteed financial forecasts.
Do not skip the compliance and data-ownership gate before designing a monetization scheme.
Do not expect the skill to connect to live systems or replace licensed institutions and regulators.