Price Data Products with Defensible Models
Data products often lack clear costs, comparable offers, and stable buyer value. This skill builds evidence-based price ranges, commercial structures, and negotiation plans.
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Review the Skillstore skill "data-product-pricing-expert" from https://skillstore.io/skills/dhturing-data-product-pricing-expert.md and its manifest at https://skillstore.io/api/skills/dhturing-data-product-pricing-expert/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Ваш Агент по-прежнему должен показать план и запросить все подтверждения, требуемые политикой безопасности.
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Использование «data-product-pricing-expert». Annual costs are CNY 240,000. Target markup is 25%. Buyer savings are CNY 4 million. Comparable offers range from CNY 280,000 to 360,000.
Ожидаемый результат:
Использование «data-product-pricing-expert». The API receives seasonal traffic, updates weekly, and serves a buyer seeking low initial commitment.
Ожидаемый результат:
Использование «data-product-pricing-expert». An enterprise buyer says the quote is too expensive but will not share a budget.
Ожидаемый результат:
All 12 static findings are false positives caused by documentation paths, Markdown backticks, ordinary website links, and dense Chinese UTF-8 text. The reviewed files contain no executable code, network requests, hidden file operations, encoded payloads, or prompt injection attempts.
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https://skillstore.io/skills/dhturing-data-product-pricing-expert/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/dhturing-data-product-pricing-expert?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/dhturing-data-product-pricing-expert?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-data-product-pricing-expert/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/dhturing-data-product-pricing-expert.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>图灵数盟. (2026). data-product-pricing-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-product-pricing-expert/audits/1@techreport{dhturing-data-product-pricing-expert-2026,
author = {图灵数盟},
title = {data-product-pricing-expert security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/dhturing-data-product-pricing-expert/audits/1},
note = {Author version unspecified}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "data-product-pricing-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-product-pricing-expert/audits/1"
identifiers:
- type: other
value: "skillstore:dhturing-data-product-pricing-expert:audit:1"
description: "Skillstore immutable audit report identifier"
Compare cost, buyer value, and market evidence before choosing a launch range and billing model.
Create anchor, target, and floor positions with concession rules for a complex buyer discussion.
Assess cost, usage, customer value, and competitive changes before recommending a price adjustment.
I sell [data product] to [buyer]. Costs are [costs], and expected buyer value is [value]. Estimate a price range and state assumptions.
Compare subscription, usage, tiered, and hybrid pricing for [product]. Recommend one model using [usage pattern], [update frequency], and [buyer constraints].
Build anchor, target, and floor prices for [product] using [cost], [buyer value], and [market comparables]. Add decreasing concessions and non-price tradeoffs.
Create a pricing decision memo for [product] across [segments]. Apply cost, value, and market methods. Show sensitivities, compliance risks, evidence gaps, and review triggers.
Автор
图灵数盟Лицензия
MIT
Ревизия Skillstore
r1
Примечание о версии
Автор не указал версию.
Ссылка
50b73f83991cf073cbdf3f5afad2bbac71dd3bae
Актуальность поддержки
30.09.2026
Использование
0 загрузок · 0 просмотров
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