Is Data Query Agent Safe?
Data Query Agent — Nerq Trust Score 62.2/100 (C grade). Based on analysis of 5 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-05-13.
Use Data Query Agent with some caution. Data Query Agent is a software tool with a Nerq Trust Score of 62.2/100 (C), based on 5 independent data dimensions. Below the recommended threshold of 70. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-05-13. Machine-readable data (JSON).
Is Data Query Agent safe?
CAUTION — Data Query Agent has a Nerq Trust Score of 62.2/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
What is Data Query Agent's trust score?
Data Query Agent has a Nerq Trust Score of 62.2/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Data Query Agent?
Data Query Agent's strongest signal is compliance at 82/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Data Query Agent and who maintains it?
| Author | cotimolinacf-beep |
| Category | Data |
| Source | https://github.com/cotimolinacf-beep/data-query-agent |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 82/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in data
What Is Data Query Agent?
Data Query Agent is a software tool in the data category: Agente para chatear con tus datos. Nerq Trust Score: 62/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Data Query Agent's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Data Query Agent performs in each:
- Security (0/100): Data Query Agent's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Data Query Agent is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (82/100): Data Query Agent is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 62.2/100 (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 Query Agent?
Data Query 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 Query Agent is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Data Query Agent's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Data Query Agent's dependency tree. - Review permissions — Understand what access Data Query Agent requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Data Query 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-query-agent - Review the license — Confirm that Data Query 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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Data Query Agent
When evaluating whether Data Query Agent is safe, consider these category-specific risks:
Understand how Data Query Agent processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Data Query Agent's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Data Query Agent. Security patches and bug fixes are only effective if you're running the latest version.
If Data Query 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 Query 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 Query Agent in violation of its license can expose your organization to legal liability.
Data Query Agent and the EU AI Act
Data Query 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 compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
Best Practices for Using Data Query Agent Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Data Query Agent while minimizing risk:
Periodically review how Data Query Agent is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Data Query Agent and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Data Query Agent only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Data Query Agent's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Data Query Agent is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Data Query Agent?
Even promising tools aren't right for every situation. Consider avoiding Data Query Agent in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Data Query Agent's trust score of 62.2/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Data Query Agent Compares 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 Query Agent's score of 62.2/100 is above the category average of 62/100.
This positions Data Query Agent favorably among data tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate 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 Query 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 maintenance patterns change, Data Query 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 security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Data Query Agent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=data-query-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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Data Query Agent are strengthening or weakening over time.
Data Query Agent vs Alternatives
In the data category, Data Query Agent scores 62.2/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Data Query Agent vs firecrawl — Trust Score: 58.8/100
- Data Query Agent vs MinerU — Trust Score: 63.7/100
- Data Query Agent vs mindsdb — Trust Score: 49.3/100
Key Takeaways
- Data Query Agent has a Trust Score of 62.2/100 (C) and is not yet Nerq Verified.
- Data Query Agent shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among data tools, Data Query Agent scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 0/100 |
| Maintenance | 1/100 |
| Popularity | 0/100 |
Based on 3 dimensions. Data from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Data Query Agent collect?
Privacy assessment for Data Query Agent is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Data Query Agent secure?
Security score: 0/100. Review security practices and consider alternatives with higher security scores for sensitive use cases.
Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.
Full analysis: Data Query Agent Security Report
How we calculated this score
Data Query Agent's trust score of 62.2/100 (C) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 3 independent dimensions: security (0/100), maintenance (1/100), popularity (0/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on May 13, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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See Also
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.