Compétences data-quality-assessment-expert

📦

data-quality-assessment-expert

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

Révision du contenu r1 Sûr 📁 Accès au système de fichiers⚙️ Commandes externes🌐 Accès réseau

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.

Prend en charge: Claude Codex Code(CC)

🥉 77 Bronze

Maintain this Skill? Claim it 🥉 77 Bronze

Installer avec mon Agent

Copiez cette demande dans votre Agent. Elle contient la page Skill de référence et le manifeste.

Demande d’agent

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.

Votre Agent doit toujours présenter son plan et demander toute confirmation exigée par la politique de sécurité.

Ressources lisibles par les agents

Utilisez ces liens lorsqu’un Agent IA, un crawler ou un script a besoin d’un contexte propre au lieu de lire toute la page.

Détail Markdown GET /skills/dhturing-data-quality-assessment-expert.md manifest signé GET /api/skills/dhturing-data-quality-assessment-expert/manifest lockfile signé GET /api/skills/dhturing-data-quality-assessment-expert/lockfile

Tester

Utilisation de « data-quality-assessment-expert ». Assess a customer dataset with 96% accuracy, 82% completeness, and delayed monthly updates.

Résultat attendu:

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

Utilisation de « data-quality-assessment-expert ». Explain whether a C-grade dataset should proceed to accounting recognition.

Résultat attendu:

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

Utilisation de « data-quality-assessment-expert ». Create a report outline for transaction due diligence.

Résultat attendu:

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

Audit de sécurité

Sûr

v1 • 27/09/2026 Ouvrir le rapport versionné

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.

Fichiers analysés

391

Lignes analysées

Éléments à examiner

Faux positifs ignorés

Facteurs de risque

📁 Accès au système de fichiers (2)

profile.md:38 profile.md:38

⚙️ Commandes externes (3)

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

🌐 Accès réseau (2)

SKILL.md:6 SKILL.md:12

Le dernier audit statique et sémantique terminé n’a détecté aucun constat de sécurité confirmé. Cela ne prouve pas que le skill est sans effets secondaires.

Audité par: codex

Partager et citer ce rapport

Partagez le rapport d’évaluation versionné, le badge neutre, la carte intégrable et les citations. Skillstore présente les preuves sans décider si ce Skill est sûr.

Ouvrir le rapport versionné

Copier le lien du rapport

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

Badge Markdown

[![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)

Badge HTML

<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>

Carte intégrable

<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>

Citations académiques (APA · BibTeX · CFF)

Citation APA

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

Citation BibTeX

@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"

Score Skillstore

Pourquoi ce score Niveau de confiance des preuves: Moyen

Architecture

Maintenabilité

Contenu

Communauté

Conformité aux spécifications

Ce que vous pouvez créer

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.

Essayez ces prompts

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.

Bonnes pratiques

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.

Éviter

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.