Habilidades data-quality-assessment-expert

📦

data-quality-assessment-expert

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

Revisión del contenido r1 Seguro 📁 Acceso al sistema de archivos⚙️ Comandos externos🌐 Acceso a red

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.

Compatible con: Claude Codex Code(CC)

🥉 77 Bronce

Maintain this Skill? Claim it 🥉 77 Bronce

Instalar con mi Agente

Copia esta solicitud en tu Agente. Incluye la página canónica del Skill y el manifiesto.

Solicitud de agente

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.

Tu Agente debe seguir mostrando su plan y solicitar cualquier confirmación exigida por la política de seguridad.

Recursos legibles por agentes

Usa estos enlaces cuando un agente de IA, crawler o script necesite contexto limpio en vez de leer la página completa.

Detalle Markdown GET /skills/dhturing-data-quality-assessment-expert.md Manifest firmado GET /api/skills/dhturing-data-quality-assessment-expert/manifest Lockfile firmado GET /api/skills/dhturing-data-quality-assessment-expert/lockfile

Pruébalo

Usando "data-quality-assessment-expert". Assess a customer dataset with 96% accuracy, 82% completeness, and delayed monthly updates.

Resultado esperado:

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

Usando "data-quality-assessment-expert". Explain whether a C-grade dataset should proceed to accounting recognition.

Resultado esperado:

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

Usando "data-quality-assessment-expert". Create a report outline for transaction due diligence.

Resultado esperado:

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

Auditoría de seguridad

Seguro

v1 • 27/9/2026 Abrir el informe versionado

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.

Archivos escaneados

391

Líneas analizadas

Elementos de revisión

Falsos positivos ignorados

Factores de riesgo

📁 Acceso al sistema de archivos (2)

profile.md:38 profile.md:38

⚙️ Comandos externos (3)

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

🌐 Acceso a red (2)

SKILL.md:6 SKILL.md:12

La auditoría estática y semántica completada más reciente no detectó hallazgos de seguridad confirmados. Esto no demuestra que el skill no tenga efectos secundarios.

Auditado por: codex

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Abrir el informe versionado

Copiar enlace del informe

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

Insignia 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)

Insignia 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>

Tarjeta para insertar

<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>

Citas académicas (APA · BibTeX · CFF)

Cita 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

Cita 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"

Puntuación de Skillstore

Por qué esta puntuación Confianza de la evidencia: Medio

Arquitectura

Mantenibilidad

Contenido

Comunidad

Cumplimiento de la especificación

Lo que puedes crear

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.

Prueba estos 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.

Mejores prácticas

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.

Evitar

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.