data-supply-demand-matching-expert
Build a Data Supply-Demand Matching System
Unstructured demand and resource records make reliable matching slow and inconsistent. This skill provides database designs, matching states, operating procedures, and review checks.
使用我的智慧代理安裝
將此請求複製給你的智慧代理,其中包含權威 Skill 頁面和清單。
Review the Skillstore skill "data-supply-demand-matching-expert" from https://skillstore.io/skills/dhturing-data-supply-demand-matching-expert.md and its manifest at https://skillstore.io/api/skills/dhturing-data-supply-demand-matching-expert/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.你的智慧代理仍應顯示其計畫,並依安全政策請求必要確認。
Agent 可讀資源
當 AI Agent、爬蟲或腳本需要乾淨脈絡、而不是讀取完整頁面時,請使用這些連結。
測試它
正在使用「data-supply-demand-matching-expert」。 A hospital needs monthly regional disease statistics within six weeks. The budget and decision owner are unknown.
預期結果:
Demand status: incomplete. The buyer and purpose are identifiable, but budget and decision authority need confirmation before matching. Ask who approves procurement, the budget range, required fields, geographic scope, permitted uses, and privacy constraints.
正在使用「data-supply-demand-matching-expert」。 A buyer needs a combined mobility and retail dataset. Separate compliant sources are available, but no combined product exists.
預期結果:
Matching state: C, combined match. Confirm each source's ownership and tradability, define join keys and permitted processing, assess privacy risk, estimate integration work, and record supplier responsibilities before introduction.
正在使用「data-supply-demand-matching-expert」。 Review a database with 140 demand records, many duplicates, and no update history.
預期結果:
- Adopt a lightweight CRM or searchable database because record volume exceeds the spreadsheet guideline.
- Define unique record identifiers, duplicate rules, owners, status values, and monthly review dates.
- Archive expired demand, preserve outcome reasons, and publish a monthly update log.
- Use unmatched valid demand to guide new resource acquisition.
安全審計
安全All 12 static findings are false positives caused by documented installation paths, Markdown backticks, attribution URLs, and high-entropy Chinese prose. The reviewed files contain no executable scripts, automatic network requests, encoded payloads, or prompt injection instructions.
風險因素
📁 檔案系統存取 (2)
⚙️ 外部命令 (3)
🌐 網路存取 (2)
分享與引用此報告
分享版本化評估報告、中性徽章、嵌入卡片與引用。Skillstore 只報告證據,不判斷該 Skill 是否安全。
複製報告連結
https://skillstore.io/skills/dhturing-data-supply-demand-matching-expert/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown 徽章
[](https://skillstore.io/skills/dhturing-data-supply-demand-matching-expert?utm_source=security_passport_badge)HTML 徽章
<a href="https://skillstore.io/skills/dhturing-data-supply-demand-matching-expert?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-data-supply-demand-matching-expert/security.svg" alt="Skillstore security assessment" loading="lazy"></a>嵌入卡片
<iframe src="https://skillstore.io/embed/skills/dhturing-data-supply-demand-matching-expert.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>學術引用 (APA · BibTeX · CFF)
APA 引用
图灵数盟. (2026). data-supply-demand-matching-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-supply-demand-matching-expert/audits/1BibTeX 引用
@techreport{dhturing-data-supply-demand-matching-expert-2026,
author = {图灵数盟},
title = {data-supply-demand-matching-expert security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/dhturing-data-supply-demand-matching-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-supply-demand-matching-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-supply-demand-matching-expert/audits/1"
identifiers:
- type: other
value: "skillstore:dhturing-data-supply-demand-matching-expert:audit:1"
description: "Skillstore immutable audit report identifier"
Skillstore 評分
評分依據 證據置信度: 中你可以打造什麼
Structure an Early Data Marketplace
Define three connected databases, practical fields, tags, and an operating sequence for a new matching program.
Assess a New Buyer Request
Check demand completeness, assign a matching state, and identify the next action and missing evidence.
Review Portfolio Gaps
Analyze unmatched demand and stale records to prioritize resource acquisition and database maintenance.
試試這些提示
Review this demand record: [record]. Check buyer identity, purpose, budget, timing, and decision chain. List missing fields and propose clarifying questions.
Design resource, demand, and expert databases for [organization]. Provide fields, definitions, required status, tags, update owners, and maintenance frequency.
Compare this demand [details] with these resources [details]. Assign matching state A-E, explain evidence, identify compliance gates, and create an action plan.
Audit these demand, resource, expert, and outcome records: [records]. Measure coverage, precision, outcomes, aging, and gaps. Recommend quarterly priorities with assumptions.
最佳實務
- Record evidence, assumptions, ownership status, and permitted uses before recommending a match.
- Prioritize complete demand records, then acquire resources that address verified unmet demand.
- Review records monthly and analyze outcomes quarterly using consistent statuses and reasons.
避免
- Do not treat vague interest without a buyer, purpose, and budget as validated demand.
- Do not recommend introductions before checking ownership, tradability, confidentiality, and qualification requirements.
- Do not build a complex platform before record volume and workflow needs justify it.
常見問題
Which database should I build first?
What makes a demand record valid?
What do matching states A through E mean?
When should I replace spreadsheets?
Does the skill contact suppliers or buyers?
Can this skill approve a data transaction?
開發者詳細資訊
作者
图灵数盟授權
MIT
Skillstore 修訂
r1
版本提示
作者未聲明版本。
引用
50b73f83991cf073cbdf3f5afad2bbac71dd3bae
維護新鮮度
2026/9/30
使用量
0 次下載 · 0 次瀏覽
檔案結構