Data Quality Agentは安全ですか?
Data Quality Agent — Nerq Trust Score 60.1/100 (Cグレード). 5つの信頼次元の分析に基づき、概ね安全だがいくつかの懸念があると評価されています。 最終更新:2026-04-02。
Data Quality Agentは注意して使用してください。 Data Quality Agent is a software tool のNerq信頼スコアは 60.1/100 (C), based on 5 独立したデータ次元. It is below the recommended threshold of 70. セキュリティ: 0/100. メンテナンス: 1/100. Popularity: 0/100. データソース: multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. 最終更新: 2026-04-02. 機械可読データ(JSON).
Data Quality Agentは安全ですか?
CAUTION — Data Quality Agent のNerq信頼スコアは 60.1/100 (C). 中程度の信頼シグナルがありますが、一部懸念される領域があります that warrant attention. Suitable for development use — review セキュリティ and メンテナンス signals before production deployment.
Data Quality Agentの信頼スコアは?
Data Quality AgentのNerq信頼スコアは60.1/100で、Cグレードです。このスコアはセキュリティ、メンテナンス、コミュニティ採用を含む5の独立した次元に基づいています。
Data Quality Agentの主なセキュリティ調査結果は?
Data Quality Agentの最も強いシグナルはコンプライアンスで100/100です。 既知の脆弱性は検出されていません。 Nerq認証閾値70+にまだ達していません。
Data Quality Agentとは何で、誰が管理していますか?
| 作者 | shotapentaho |
| カテゴリ | data |
| Source | https://github.com/shotapentaho/data-quality-agent |
| Protocols | rest |
規制コンプライアンス
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| 管轄権s | Assessed across 52 管轄s |
dataの人気の代替品
What Is Data Quality Agent?
Data Quality Agent is a software tool in the data category: AI-Powered Data Quality Analysis & Insights - A modular, enterprise-grade Streamlit application.. Nerq Trust Score: 60/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including セキュリティ vulnerabilities, メンテナンス activity, license コンプライアンス, and コミュニティでの採用.
How Nerq Assesses Data Quality Agent's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five 次元. Here is how Data Quality Agent performs in each:
- セキュリティ (0/100): Data Quality Agent's セキュリティ posture is poor. This score factors in known CVEs, dependency vulnerabilities, セキュリティ policy presence, and code signing practices.
- メンテナンス (1/100): Data Quality Agent is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API ドキュメント, usage examples, and contribution guidelines.
- Compliance (100/100): Data Quality Agent is broadly compliant. Assessed against regulations in 52 管轄s including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. に基づく GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 60.1/100 (C) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Data Quality Agent?
Data Quality Agent is designed for:
- Developers and teams working with data tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Data Quality Agent is suitable for development and testing environments. Before production deployment, conduct a thorough review of its セキュリティ posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Data Quality Agent's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — 確認してください repository's セキュリティ policy, open issues, and recent commits for signs of active メンテナンス.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Data Quality Agent's dependency tree. - レビュー permissions — Understand what access Data Quality Agent requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Data Quality Agent in a sandboxed environment before granting access to production data or systems.
- Monitor continuously — Use Nerq's API to set up automated trust checks:
GET nerq.ai/v1/preflight?target=data-quality-agent - 確認してください license — Confirm that Data Quality Agent's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
- Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses セキュリティ concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Data Quality Agent
When evaluating whether Data Quality Agent is safe, consider these category-specific risks:
Understand how Data Quality Agent processes, stores, and transmits your data. 確認してください tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Data Quality Agent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher セキュリティ risk.
Regularly check for updates to Data Quality Agent. セキュリティ patches and bug fixes are only effective if you're running the latest version.
If Data Quality Agent connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.
Verify that Data Quality Agent's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Data Quality Agent in violation of its license can expose your organization to legal liability.
Data Quality Agent and the EU AI Act
Data Quality Agent is classified as Minimal Risk under the EU AI Act. This is the lowest risk category, meaning it faces minimal regulatory requirements. However, transparency obligations still apply.
Nerq's コンプライアンス assessment covers 52 管轄s worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal コンプライアンス.
Best Practices for Using Data Quality Agent Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Data Quality Agent while minimizing risk:
Periodically review how Data Quality Agent is used in your workflow. Check for unexpected behavior, permissions drift, and コンプライアンス with your セキュリティ policies.
Ensure Data Quality Agent and all its dependencies are running the latest stable versions to benefit from セキュリティ patches.
Grant Data Quality Agent only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Data Quality Agent's セキュリティ advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Data Quality Agent is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Data Quality Agent?
Even promising tools aren't right for every situation. Consider avoiding Data Quality Agent in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional コンプライアンス review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Data Quality Agentの信頼スコア 60.1/100 meets your organization's risk tolerance. We recommend running a manual セキュリティ assessment alongside the automated Nerq score.
How Data Quality Agent 比較s to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among data tools, the average Trust Score is 62/100. Data Quality Agent's score of 60.1/100 is near the category average of 62/100.
This places Data Quality Agent in line with the typical data tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks 中程度 in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.
Trust Score History
Nerq continuously monitors Data Quality Agent and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or メンテナンス patterns change, Data Quality Agent's score is updated within 24 hours.
Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to セキュリティ and quality. Conversely, a downward trend may signal reduced メンテナンス, growing technical debt, or unresolved vulnerabilities. To track Data Quality Agent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=data-quality-agent&include=history
Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — セキュリティ, メンテナンス, ドキュメント, コンプライアンス, and community — has evolved independently, providing granular visibility into which aspects of Data Quality Agent are strengthening or weakening over time.
Data Quality Agent vs 代替品
In the data category, Data Quality Agent scores 60.1/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Data Quality Agent vs firecrawl — Trust Score: 73.8/100
- Data Quality Agent vs MinerU — Trust Score: 84.6/100
- Data Quality Agent vs mindsdb — Trust Score: 77.5/100
重要なポイント
- Data Quality Agent の信頼スコアは 60.1/100 (C) and is not yet Nerq Verified.
- Data Quality Agent shows 中程度 trust signals. Conduct thorough due diligence before deploying to production environments.
- Among data tools, Data Quality Agent scores near the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
よくある質問
Is Data Quality Agent 安全に使用できます?
Data Quality Agent's trust scoreとは?
Data Quality Agentのより安全な代替品は?
How often is Data Quality Agent's safety score updated?
Can I use Data Quality Agent in a regulated environment?
Disclaimer: Nerqの信頼スコアは、公開されている情報に基づく自動評価です。推奨や保証ではありません。必ずご自身でも確認してください。