Opencode Skill安全吗?
Opencode Skill — Nerq 信任评分 62.2/100 (C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:2026-04-02。
请谨慎使用Opencode Skill。 Opencode Skill is a software tool Nerq 信任评分为 62.2/100 (C), based on 5 独立数据维度. 低于推荐阈值 70。 安全性: 0/100. 维护: 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: 2026-04-02. 机器可读数据(JSON).
Opencode Skill安全吗?
谨慎 — Opencode Skill Nerq 信任评分为 62.2/100 (C). 信任信号中等,但存在一些值得关注的方面. 适合用于开发环境 — 在生产部署前请查看安全性和维护信号.
Opencode Skill的信任评分是多少?
Opencode Skill Nerq 信任评分为 62.2/100, earning a C grade. This score is based on 5 independently measured 维度 including 安全性, 维护, and 社区采用.
Opencode Skill的主要安全发现是什么?
Opencode Skill's strongest signal is 合规性 at 96/100. No 已知漏洞 have been detected. It has not yet reached the Nerq Verified threshold of 70+.
Opencode Skill是什么,谁在维护它?
| 开发者 | piglet-97 |
| 类别 | coding |
| 来源 | https://github.com/piglet-97/opencode-skill |
| Protocols | rest |
合规性
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 96/100 |
| 管辖权s | Assessed across 52 司法管辖区s |
coding中的热门替代品
What Is Opencode Skill?
Opencode Skill is a software tool in the coding category: OpenCode AI Coding Agent Skill for OpenClaw Framework generates, reviews, and refactors code.. Nerq 信任评分: 62/100 (C).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including 安全性 vulnerabilities, 维护 activity, license 合规性, and 社区采用.
How Nerq Assesses Opencode Skill's Safety
Nerq's 信任评分 is calculated from 13+ independent signals aggregated into five 维度. Here is how Opencode Skill performs in each:
- 安全性 (0/100): Opencode Skill's 安全性 posture is poor. This score factors in known CVEs, dependency vulnerabilities, 安全性 policy presence, and code signing practices.
- 维护 (1/100): Opencode Skill 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 文档, usage examples, and contribution guidelines.
- Compliance (96/100): Opencode Skill is broadly compliant. Assessed against regulations in 52 司法管辖区s including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. 基于 GitHub stars, forks, download counts, and ecosystem integrations.
The overall 信任评分 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 Opencode Skill?
Opencode Skill 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: Opencode Skill is suitable for development and testing environments. Before production deployment, conduct a thorough review of its 安全性 posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Opencode Skill's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — 查看 repository's 安全性 policy, open issues, and recent commits for signs of active 维护.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for 已知漏洞 in Opencode Skill's dependency tree. - 评论 permissions — Understand what access Opencode Skill requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Opencode Skill 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=opencode-skill - 查看 license — Confirm that Opencode Skill'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 安全性 concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Opencode Skill
When evaluating whether Opencode Skill is safe, consider these category-specific risks:
Understand how Opencode Skill processes, stores, and transmits your data. 查看 tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Opencode Skill's dependency tree for 已知漏洞. Tools with outdated or unmaintained dependencies pose a higher 安全性 risk.
Regularly check for updates to Opencode Skill. 安全性 patches and bug fixes are only effective if you're running the latest version.
If Opencode Skill 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 Opencode Skill's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Opencode Skill in violation of its license can expose your organization to legal liability.
Opencode Skill and the EU AI Act
Opencode Skill 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 合规性 assessment covers 52 司法管辖区s worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal 合规性.
Best Practices for Using Opencode Skill Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Opencode Skill while minimizing risk:
Periodically review how Opencode Skill is used in your workflow. Check for unexpected behavior, permissions drift, and 合规性 with your 安全性 policies.
Ensure Opencode Skill and all its dependencies are running the latest stable versions to benefit from 安全性 patches.
Grant Opencode Skill only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Opencode Skill's 安全性 advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Opencode Skill is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Opencode Skill?
Even promising tools aren't right for every situation. Consider avoiding Opencode Skill in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional 合规性 review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Opencode Skill的信任评分为 62.2/100 meets your organization's risk tolerance. We recommend running a manual 安全性 assessment alongside the automated Nerq score.
How Opencode Skill Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average 信任评分 is 62/100. Opencode Skill's score of 62.2/100 is above the category average of 62/100.
This positions Opencode Skill favorably among coding tools. While it outperforms the average, there is still room for improvement in certain trust 维度.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks 中等 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.
信任评分 History
Nerq continuously monitors Opencode Skill and recalculates its 信任评分 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 维护 patterns change, Opencode Skill'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 安全性 and quality. Conversely, a downward trend may signal reduced 维护, growing technical debt, or unresolved vulnerabilities. To track Opencode Skill's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=opencode-skill&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 — 安全性, 维护, 文档, 合规性, and community — has evolved independently, providing granular visibility into which aspects of Opencode Skill are strengthening or weakening over time.
Opencode Skill vs 替代品
In the coding category, Opencode Skill scores 62.2/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Opencode Skill vs AutoGPT — 信任评分: 74.7/100
- Opencode Skill vs ollama — 信任评分: 73.8/100
- Opencode Skill vs langchain — 信任评分: 86.4/100
主要结论
- Opencode Skill has a 信任评分 of 62.2/100 (C) and is not yet Nerq Verified.
- Opencode Skill shows 中等 trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Opencode Skill 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.
常见问题
Opencode Skill可以安全使用吗?
Opencode Skill's trust score是什么?
Opencode Skill有哪些更安全的替代品?
How often is Opencode Skill's safety score updated?
我可以在受监管环境中使用Opencode Skill吗?
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。