Agentsqlmemory est-il sûr ?
Agentsqlmemory — Nerq Trust Score 64.6/100 (Note C). Sur la base de l'analyse de 5 dimensions de confiance, il est généralement sûr mais avec quelques préoccupations. Dernière mise à jour : 2026-04-25.
Utilisez Agentsqlmemory avec précaution. Agentsqlmemory est un software tool avec un Nerq Trust Score de 64.6/100 (C), basé sur 5 dimensions de données indépendantes. En dessous du seuil vérifié Nerq Sécurité: 0/100. Maintenance: 1/100. Popularité: 0/100. Données de plusieurs sources publiques dont les registres de paquets, GitHub, NVD, OSV.dev et OpenSSF Scorecard. Dernière mise à jour: 2026-04-25. Données lisibles par machine (JSON).
Agentsqlmemory est-il sûr ?
CAUTION — Agentsqlmemory has a Nerq Trust Score of 64.6/100 (C). Il présente des signaux de confiance modérés mais montre certaines zones de préoccupation that warrant attention. Suitable for development use — review sécurité and maintenance signals before production deployment.
Quel est le score de confiance de Agentsqlmemory ?
Agentsqlmemory a un Score de Confiance Nerq de 64.6/100, obtenant la note C. Ce score est basé sur 5 dimensions mesurées indépendamment.
Quels sont les résultats de sécurité clés pour Agentsqlmemory ?
Le signal le plus fort de Agentsqlmemory est conformité à 87/100. Aucune vulnérabilité connue n'a été détectée. N'a pas encore atteint le seuil vérifié Nerq de 70+.
Qu'est-ce que Agentsqlmemory et qui le maintient ?
| Auteur | mikeNickaloff |
| Catégorie | Coding |
| Source | https://github.com/mikeNickaloff/AgentSQLMemory |
| Frameworks | openai · anthropic |
| Protocols | rest |
Conformité réglementaire
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 87/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternatives populaires dans coding
What Is Agentsqlmemory?
Agentsqlmemory is a software tool in the coding category: AgentSQLMemory extends AI coding assistants' memory for code intelligence.. Nerq Trust Score: 65/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including sécurité vulnerabilities, maintenance activity, license conformité, and adoption par la communauté.
How Nerq Assesses Agentsqlmemory's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Agentsqlmemory performs in each:
- Sécurité (0/100): Agentsqlmemory's sécurité posture is poor. This score factors in known CVEs, dependency vulnerabilities, sécurité policy presence, and code signing practices.
- Maintenance (1/100): Agentsqlmemory 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 documentation, usage examples, and contribution guidelines.
- Compliance (87/100): Agentsqlmemory is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Basé sur GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 64.6/100 (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 Agentsqlmemory?
Agentsqlmemory is designed for:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Agentsqlmemory is suitable for development and testing environments. Before production deployment, conduct a thorough review of its sécurité posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Agentsqlmemory's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Examiner le/la repository's sécurité 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 Agentsqlmemory's dependency tree. - Avis permissions — Understand what access Agentsqlmemory requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Agentsqlmemory 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=AgentSQLMemory - Examiner le/la license — Confirm that Agentsqlmemory'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 sécurité concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Agentsqlmemory
When evaluating whether Agentsqlmemory is safe, consider these category-specific risks:
Understand how Agentsqlmemory processes, stores, and transmits your data. Examiner le/la tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Agentsqlmemory's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher sécurité risk.
Regularly check for updates to Agentsqlmemory. Sécurité patches and bug fixes are only effective if you're running the latest version.
If Agentsqlmemory 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 Agentsqlmemory's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Agentsqlmemory in violation of its license can expose your organization to legal liability.
Agentsqlmemory and the EU AI Act
Agentsqlmemory 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 conformité assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal conformité.
Best Practices for Using Agentsqlmemory Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Agentsqlmemory while minimizing risk:
Periodically review how Agentsqlmemory is used in your workflow. Check for unexpected behavior, permissions drift, and conformité with your sécurité policies.
Ensure Agentsqlmemory and all its dependencies are running the latest stable versions to benefit from sécurité patches.
Grant Agentsqlmemory only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Agentsqlmemory's sécurité advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Agentsqlmemory is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Agentsqlmemory?
Even promising tools aren't right for every situation. Consider avoiding Agentsqlmemory in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional conformité review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Agentsqlmemory's trust score of 64.6/100 meets your organization's risk tolerance. We recommend running a manual sécurité assessment alongside the automated Nerq score.
How Agentsqlmemory Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Agentsqlmemory's score of 64.6/100 is above the category average of 62/100.
This positions Agentsqlmemory favorably among coding 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 modéré 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 Agentsqlmemory 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, Agentsqlmemory'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 sécurité and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Agentsqlmemory's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=AgentSQLMemory&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 — sécurité, maintenance, documentation, conformité, and community — has evolved independently, providing granular visibility into which aspects of Agentsqlmemory are strengthening or weakening over time.
Agentsqlmemory vs Alternatives
In the coding category, Agentsqlmemory scores 64.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Agentsqlmemory vs AutoGPT — Trust Score: 74.7/100
- Agentsqlmemory vs ollama — Trust Score: 73.8/100
- Agentsqlmemory vs langchain — Trust Score: 71.3/100
Points Essentiels
- Agentsqlmemory has a Trust Score of 64.6/100 (C) and is not yet Nerq Verified.
- Agentsqlmemory shows modéré trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Agentsqlmemory 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.
Analyse détaillée du score
| Dimension | Score |
|---|---|
| Sécurité | 0/100 |
| Maintenance | 1/100 |
| Popularité | 0/100 |
Basé sur 3 dimensions. Data from plusieurs sources publiques dont les registres de paquets, GitHub, NVD, OSV.dev et OpenSSF Scorecard.
Quelles données Agentsqlmemory collecte-t-il ?
Confidentialité assessment for Agentsqlmemory is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Agentsqlmemory est-il sécurisé ?
Sécurité score: 0/100. Review sécurité practices and consider alternatives with higher sécurité scores for sensitive use cases.
Nerq surveille cette entité par rapport à NVD, OSV.dev et aux bases de données de vulnérabilités spécifiques aux registres pour une évaluation de sécurité continue.
Analyse complète : Rapport de sécurité de Agentsqlmemory
Comment nous avons calculé ce score
Agentsqlmemory's trust score of 64.6/100 (C) est calculé à partir de plusieurs sources publiques dont les registres de paquets, GitHub, NVD, OSV.dev et OpenSSF Scorecard. Le score reflète 3 dimensions indépendantes: sécurité (0/100), maintenance (1/100), popularité (0/100). Chaque dimension est pondérée de manière égale pour produire le score de confiance composite.
Nerq analyse plus de 7,5 millions d'entités dans 26 registres en utilisant la même méthodologie, permettant une comparaison directe entre entités. Les scores sont mis à jour en continu dès que de nouvelles données sont disponibles.
Cette page a été révisée pour la dernière fois le April 25, 2026. Version des données: 1.0.
Documentation complète de la méthodologie · Données lisibles par machine (API JSON)
Questions fréquentes
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Voir aussi
Disclaimer: Les scores de confiance Nerq sont des évaluations automatisées basées sur des signaux publiquement disponibles. Ce ne sont pas des recommandations ou des garanties. Effectuez toujours votre propre vérification.