Skillos安全吗?

Skillos — Nerq Trust Score 70.5/100 (B级). 基于5个信任维度的分析,被评估为总体安全但存在一些担忧。 最后更新:2026-04-05。

是的,Skillos可以安全使用。 Skillos 是一个software tool Nerq 信任分数 70.5/100(B), 基于5个独立数据维度. It is 推荐使用. Security: 0/100. Maintenance: 1/100. 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).

Skillos安全吗?

YES — Skillos has a Nerq Trust Score of 70.5/100 (B). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. 推荐使用 — review the full report below for specific considerations.

安全分析 → {name}隐私报告 →

Skillos的信任评分是多少?

Skillos 的 Nerq 信任分数为 70.5/100,等级为 B。该分数基于 5 个独立测量的维度,包括安全性、维护和社区采用。

安全性
0
合规性
100
维护
1
文档
1
人气
0

Skillos的主要安全发现是什么?

Skillos 最强的信号是 合规性,为 100/100。 未检测到已知漏洞。 达到 Nerq 认证阈值 70+。

Security score: 0/100 (weak)
Maintenance: 1/100 — low maintenance activity
Compliance: 100/100 — covers 52 of 52 jurisdictions
Documentation: 1/100 — limited documentation
Popularity: 0/100 — community adoption

Skillos是什么,谁在维护它?

开发者AlexeyPevz
类别devops
来源https://github.com/AlexeyPevz/SkillOS
Protocolsrest

合规性

EU AI Act Risk ClassMINIMAL
Compliance Score100/100
JurisdictionsAssessed across 52 jurisdictions

devops中的热门替代品

ansible/ansible
84.3/100 · A
github
FlowiseAI/Flowise
76.9/100 · B
github
shareAI-lab/learn-claude-code
81.5/100 · A
github
continuedev/continue
84.4/100 · A
github
wshobson/agents
88.7/100 · A
github

What Is Skillos?

Skillos is a DevOps tool: Self-hosted AI agent orchestration framework. Nerq Trust Score: 70/100 (B).

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 Skillos's Safety

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

The overall Trust Score of 70.5/100 (B) reflects the weighted combination of these signals. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use.

Who Should Use Skillos?

Skillos is designed for:

Risk guidance: Skillos meets the minimum threshold for production use, but we recommend monitoring for security advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.

How to Verify Skillos'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's 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 Skillos's dependency tree.
  3. Review permissions — Understand what access Skillos requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Skillos 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=SkillOS
  6. Review the license — Confirm that Skillos'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 Skillos

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

Data handling

Understand how Skillos 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 Skillos's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

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

Third-party integrations

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

Skillos and the EU AI Act

Skillos 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 Skillos Safely

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

Conduct regular audits

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

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

Subscribe to Skillos'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 Skillos is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Skillos?

Even well-trusted tools aren't right for every situation. Consider avoiding Skillos in these scenarios:

For each scenario, evaluate whether Skillos's trust score of 70.5/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Skillos Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among DevOps tools, the average Trust Score is 63/100. Skillos's score of 70.5/100 is above the category average of 63/100.

This positions Skillos favorably among DevOps 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 Skillos 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, Skillos'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 Skillos's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=SkillOS&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 Skillos are strengthening or weakening over time.

Skillos vs Alternatives

In the devops category, Skillos scores 70.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Key Takeaways

常见问题

Is Skillos safe to use?
Yes, it is safe to use. SkillOS has a Nerq Trust Score of 70.5/100 (B). Strongest signal: 合规性 (100/100). Score based on security (0/100), maintenance (1/100), popularity (0/100), documentation (1/100).
What is Skillos's trust score?
SkillOS: 70.5/100 (B). Score based on: security (0/100), maintenance (1/100), popularity (0/100), documentation (1/100). Compliance: 100/100. Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=SkillOS
What are safer alternatives to Skillos?
In the devops category, higher-rated alternatives include ansible/ansible (84/100), FlowiseAI/Flowise (77/100), shareAI-lab/learn-claude-code (82/100). SkillOS scores 70.5/100.
How often is Skillos's safety score updated?
Nerq continuously monitors Skillos 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: 70.5/100 (B), last verified 2026-04-05. API: GET nerq.ai/v1/preflight?target=SkillOS
Can I use Skillos in a regulated environment?
Yes — Skillos meets the Nerq Verified threshold (70+). Combine this with your internal security review for regulated deployments.
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。

我们使用Cookie进行分析和缓存。 隐私