Agentskb安全吗?

Agentskb — Nerq Trust Score 42.5/100 (E级). 基于3个信任维度的分析,被评估为存在值得注意的安全问题。 最后更新:2026-04-05。

请对Agentskb保持警惕。 Agentskb 是一个software tool Nerq 信任分数 42.5/100(E), 基于3个独立数据维度. It is below the recommended threshold of 70. Maintenance: 0/100. Popularity: 0/100. 数据来源于multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard。最后更新:2026-04-05。 机器可读数据(JSON).

Agentskb安全吗?

NO — USE WITH CAUTION — Agentskb has a Nerq Trust Score of 42.5/100 (E). It has below-average trust signals with significant gaps in security, maintenance, or documentation. Not recommended for production use without thorough manual review and additional security measures.

安全分析 → {name}隐私报告 →

Agentskb的信任评分是多少?

Agentskb 的 Nerq 信任分数为 42.5/100,等级为 E。该分数基于 3 个独立测量的维度,包括安全性、维护和社区采用。

维护
0
文档
0
人气
0

Agentskb的主要安全发现是什么?

Agentskb 最强的信号是 维护,为 0/100。 未检测到已知漏洞。 尚未达到 Nerq 认证阈值 70+。

Maintenance: 0/100 — low maintenance activity
Documentation: 0/100 — limited documentation
Popularity: 0/100 — 7 stars on pulsemcp

Agentskb是什么,谁在维护它?

开发者https://github.com/cranot/agentskb-mcp
类别knowledge|research
星标7
来源https://github.com/cranot/agentskb-mcp
Protocolsmcp

What Is Agentskb?

Agentskb is a software tool in the knowledge|research category: Expert-level knowledge base with researched answers from official sources. It has 7 GitHub stars. Nerq Trust Score: 42/100 (E).

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 Agentskb's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Agentskb performs in each:

The overall Trust Score of 42.5/100 (E) 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 Agentskb?

Agentskb is designed for:

Risk guidance: We recommend caution with Agentskb. The low trust score suggests potential risks in security, maintenance, or community support. Consider using a more established alternative for any production or sensitive workload.

How to Verify Agentskb's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Agentskb's dependency tree.
  3. Review permissions — Understand what access Agentskb requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Agentskb in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=AgentsKB
  6. Review the license — Confirm that Agentskb'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.
  7. 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 Agentskb

When evaluating whether Agentskb is safe, consider these category-specific risks:

Data handling

Understand how Agentskb processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency security

Check Agentskb's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

Regularly check for updates to Agentskb. Security patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Agentskb 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.

License and IP compliance

Verify that Agentskb's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Agentskb in violation of its license can expose your organization to legal liability.

Best Practices for Using Agentskb Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Agentskb while minimizing risk:

Conduct regular audits

Periodically review how Agentskb is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

Ensure Agentskb and all its dependencies are running the latest stable versions to benefit from security patches.

Follow least privilege

Grant Agentskb only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for security advisories

Subscribe to Agentskb's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Agentskb is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Agentskb?

Even promising tools aren't right for every situation. Consider avoiding Agentskb in these scenarios:

For each scenario, evaluate whether Agentskb's trust score of 42.5/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Agentskb Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among knowledge|research tools, the average Trust Score is 62/100. Agentskb's score of 42.5/100 is below the category average of 62/100.

This suggests that Agentskb trails behind many comparable knowledge|research tools. Organizations with strict security requirements should evaluate whether higher-scoring alternatives better meet their needs.

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 Agentskb 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, Agentskb'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 Agentskb's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=AgentsKB&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 Agentskb are strengthening or weakening over time.

Key Takeaways

常见问题

Is Agentskb safe to use?
Exercise caution. AgentsKB has a Nerq Trust Score of 42.5/100 (E). Strongest signal: 维护 (0/100). Score based on maintenance (0/100), popularity (0/100), documentation (0/100).
What is Agentskb's trust score?
AgentsKB: 42.5/100 (E). Score based on: maintenance (0/100), popularity (0/100), documentation (0/100). Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=AgentsKB
What are safer alternatives to Agentskb?
In the knowledge|research category, more software tools are being analyzed — check back soon. AgentsKB scores 42.5/100.
How often is Agentskb's safety score updated?
Nerq continuously monitors Agentskb and updates its trust score as new data becomes available. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Current: 42.5/100 (E), last verified 2026-04-05. API: GET nerq.ai/v1/preflight?target=AgentsKB
Can I use Agentskb in a regulated environment?
Agentskb has not reached the Nerq Verified threshold of 70. Additional due diligence is recommended for regulated environments.
API: /v1/preflight Trust Badge API Docs

Disclaimer: Nerq 信任评分是基于公开信号的自动评估。它们不构成建议或保证。请始终进行自己的验证。

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