Fähigkeiten data-quality-assessment-expert

📦

data-quality-assessment-expert

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

Inhaltsrevision r1 Sicher 📁 Dateisystemzugriff⚙️ Externe Befehle🌐 Netzwerkzugriff

Assess Data Quality with Six-Dimension Scoring

Unclear data quality weakens asset, transaction, and governance decisions. This skill scores six dimensions, assigns grades, and recommends focused remediation.

Unterstützt: Claude Codex Code(CC)

🥉 77 Bronze

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Mit meinem Agent installieren

Kopieren Sie diese Anfrage in Ihren Agent. Sie enthält die maßgebliche Skill-Seite und das Manifest.

Agent-Anfrage

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

Ihr Agent sollte weiterhin seinen Plan anzeigen und alle von der Sicherheitsrichtlinie verlangten Bestätigungen anfordern.

Agent-lesbare Ressourcen

Verwenden Sie diese Links, wenn ein KI-Agent, Crawler oder Skript sauberen Kontext benötigt, statt die vollständige Seite zu lesen.

Markdown-Detailseite GET /skills/dhturing-data-quality-assessment-expert.md Signiertes manifest GET /api/skills/dhturing-data-quality-assessment-expert/manifest Signiertes lockfile GET /api/skills/dhturing-data-quality-assessment-expert/lockfile

Testen

„data-quality-assessment-expert“ wird verwendet. Assess a customer dataset with 96% accuracy, 82% completeness, and delayed monthly updates.

Erwartetes Ergebnis:

The assessment highlights strong accuracy, weak completeness, and material timeliness risk. It recommends filling critical fields and enforcing update deadlines before final grading.

„data-quality-assessment-expert“ wird verwendet. Explain whether a C-grade dataset should proceed to accounting recognition.

Erwartetes Ergebnis:

A C grade indicates material quality gaps. Complete targeted remediation and reassessment before recognition, while documenting evidence, ownership, and remaining limitations.

„data-quality-assessment-expert“ wird verwendet. Create a report outline for transaction due diligence.

Erwartetes Ergebnis:

Purpose, scope, and evaluation date
Standards, methods, sampling, and rules
Six-dimension results and issue evidence
Weighted score, grade, and reference delta range
Remediation plan, limitations, and appendices

Sicherheitsaudit

Sicher

v1 • 27.9.2026 Versionsbericht öffnen

All twelve static findings are false positives caused by Markdown formatting, installation documentation, ordinary website links, and the entropy of Chinese-language text. No executable scripts, network requests, obfuscated payloads, prompt injection, or unsafe data-handling intent were found.

Gescannte Dateien

391

Analysierte Zeilen

Prüfelemente

Falschmeldungen ignoriert

Risikofaktoren

📁 Dateisystemzugriff (2)

profile.md:38 profile.md:38

⚙️ Externe Befehle (3)

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

🌐 Netzwerkzugriff (2)

SKILL.md:6 SKILL.md:12

Das letzte abgeschlossene statische und semantische Audit erkannte keine bestätigten Sicherheitsbefunde. Dies beweist nicht, dass der Skill keine Nebenwirkungen hat.

Geprüft von: codex

Diesen Bericht teilen & zitieren

Teile den versionierten Bewertungsbericht, das neutrale Badge, die Einbettungskarte und Zitate. Skillstore berichtet Nachweise, ohne zu entscheiden, ob dieser Skill sicher ist.

Versionsbericht öffnen

Berichtslink kopieren

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

HTML-Badge

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

Einbettungskarte

<iframe src="https://skillstore.io/embed/skills/dhturing-data-quality-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>

Wissenschaftliche Zitate (APA · BibTeX · CFF)

APA-Zitat

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

BibTeX-Zitat

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

Skillstore-Score

Warum dieser Score Evidenzvertrauen: Mittel

Architektur

Wartbarkeit

Inhalt

Gemeinschaft

Spezifikationskonformität

Was Sie erstellen können

Prepare data for accounting recognition

Build a six-dimension assessment, document evidence, and identify quality gaps before data resource recognition.

Support buyer due diligence

Evaluate transaction data, explain its grade, and present reproducible checks for buyer review.

Prioritize quality remediation

Rank defects by severity and define focused actions for the weakest quality dimensions.

Diese Prompts ausprobieren

Create a basic quality checklist

Create a six-dimension data quality checklist for [dataset]. State one measurable indicator and one evidence source for each dimension.

Design a weighted scorecard

Design a GB/T 36344-2018 scorecard for [purpose]. Explain each weight, scoring rule, threshold, and required evidence.

Analyze assessment results

Assess these quality results: [results]. Calculate dimension scores, the weighted total, the grade, major defects, and recommended remediation priorities.

Develop an assessment and valuation package

Develop a complete assessment for [dataset and purpose]. Include scope, sampling, rules, scores, grade, delta range, caveats, remediation, and monitoring.

Bewährte Praktiken

Define the business purpose, dataset scope, evaluation date, and evidence requirements before scoring.
Use read-only access and avoid copying or retaining source data during assessment.
Document formulas, samples, thresholds, and exceptions so reviewers can reproduce every score.

Vermeiden

Do not raise scores to satisfy a preferred accounting, transaction, or valuation outcome.
Do not infer a final grade from undocumented samples or incomplete dimension results.
Do not present reference delta ranges as certified appraisal or regulatory conclusions.