Skills data-monetization-expert

📦

data-monetization-expert

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

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

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.

Supports: Claude Codex Code(CC)

🥉 77 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

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.

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-monetization-expert.md Signed manifest GET /api/skills/dhturing-data-monetization-expert/manifest Signed lockfile GET /api/skills/dhturing-data-monetization-expert/lockfile

Test it

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

Expected outcome:

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.

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

Expected outcome:

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.

Security Audit

Safe

v1 • 9/27/2026 Open versioned report

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.

Files scanned

458

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: claude

Share & cite this report

Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.

Open versioned report

Copy report link

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

Markdown badge

[![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 badge

<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>

Embed card

<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>

Academic citations (APA · BibTeX · CFF)

APA citation

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 citation

@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 Score

Why this score Evidence Confidence: Medium

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

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.

Try These Prompts

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.

Best Practices

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.

Avoid

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.