Is Go Playing Agent Safe? — Trust Score: 76.3/100

According to Nerq's independent analysis of go-playing-agent, this coding has a trust score of 76.3 out of 100, earning a B grade. With 0 stars on github, it is recommended for production use. Security score: 0/100. Compliance: 92/100 across 52 jurisdictions. EU AI Act classification: minimal. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-19. Machine-readable data (JSON).

go-playing-agent has a Nerq Trust Score of 76.3/100 (B). Recommended — meets Nerq Verified threshold. Its strongest signal is compliance (92/100). Compliance: 47 of 52 jurisdictions. EU AI Act compliant. Last verified: 2026-03-19.

Is Go Playing Agent safe?

YES — Go Playing Agent has a Nerq Trust Score of 76.3/100 (B). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.

76.3
out of 100
B coding github verified

Trust Assessment

Trusted — go-playing-agent demonstrates strong trust signals. It meets the threshold for Nerq Verified status, indicating solid security practices, active maintenance, and a healthy ecosystem presence.

Trust Signal Breakdown

Security
0
Code quality, vulnerability exposure, and security practices.
Compliance
92
Regulatory alignment. EU AI Act risk class: minimal.
Maintenance
1
Update frequency, issue responsiveness, active development.
Documentation
1
README quality, API docs, usage examples.
Popularity
0
Community adoption. 0 stars on github.

Details

Authorlaperdida23
Categorycoding
Stars0
Sourcehttps://github.com/laperdida23/go-playing-agent

Regulatory Compliance

EU AI Act Risk ClassMINIMAL
Compliance Score92/100
JurisdictionsAssessed across 52 jurisdictions

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What Is Go Playing Agent?

Go Playing Agent is a AI tool in the coding category. AI agent for playing Go on a 5x5 board with advanced algorithms.

As of March 2026, Go Playing Agent is available on github, making it an emerging tool in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.

How Nerq Assesses Go Playing Agent's Safety

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

The overall Trust Score of 76.3/100 (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 Go Playing Agent?

Go Playing Agent is designed for:

Risk guidance: Go Playing Agent 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 Go Playing Agent's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI 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 Go Playing Agent's dependency tree.
  3. Review permissions — Understand what access Go Playing Agent requires. AI tools should follow the principle of least privilege.
  4. Test in isolation — Run Go Playing Agent 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=go-playing-agent
  6. Review the license — Confirm that Go Playing 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.
  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 Go Playing Agent

When evaluating whether Go Playing Agent is safe, consider these category-specific risks:

Data handling

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

Update frequency

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

Third-party integrations

If Go Playing 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.

License and IP compliance

Verify that Go Playing 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 Go Playing Agent in violation of its license can expose your organization to legal liability.

Go Playing Agent and the EU AI Act

Go Playing 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 Go Playing Agent Safely

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

Conduct regular audits

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

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

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

When Should You Avoid Go Playing Agent?

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

For each scenario, evaluate whether Go Playing Agent's trust score of 76.3/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Go Playing Agent Compares to Industry Standards

Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among coding tools, the average Trust Score is 62/100. Go Playing Agent's score of 76.3/100 is significantly above the category average of 62/100.

This places Go Playing Agent in the top tier of coding tools that Nerq tracks. Tools scoring this far above average typically demonstrate mature security practices, consistent release cadence, and broad community adoption.

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 Go Playing 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, Go Playing 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 Go Playing Agent's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=go-playing-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 Go Playing Agent are strengthening or weakening over time.

Go Playing Agent vs Alternatives

In the coding category, Go Playing Agent scores 76.3/100. It ranks among the top tools in its category. For a detailed comparison, see:

Key Takeaways

Frequently Asked Questions

Is go-playing-agent safe to use?
go-playing-agent has a Nerq Trust Score of 76.3/100, earning a B grade. Trusted — go-playing-agent demonstrates strong trust signals. It meets the threshold for Nerq Verified status, indicating solid security practices, active maintenance, and a healthy ecosystem presence. Its strongest signal is compliance (92/100). It is Nerq Verified, meaning it meets the 70+ trust threshold. Always review the full KYA report before using any AI agent in production.
What is go-playing-agent's trust score?
Nerq assigns go-playing-agent a trust score of 76.3 out of 100, with a grade of B. This score is computed from multiple dimensions including security, compliance, maintenance activity, documentation quality, and community adoption (0 stars). Compliance score: 92/100. EU AI Act risk class: minimal. Scores are updated daily based on the latest publicly available signals.
Are there safer alternatives to go-playing-agent?
In the coding category, higher-rated alternatives include Significant-Gravitas/AutoGPT, ollama/ollama, langchain-ai/langchain (scores: 75, 74, 88). go-playing-agent scores 76.3/100. When choosing between agents, consider your specific requirements for security (N/A), maintenance activity (1), and documentation (1). Use Nerq's comparison tools or the KYA endpoint for detailed side-by-side analysis.
How often is Go Playing Agent's safety score updated?
Nerq continuously monitors Go Playing Agent and updates its trust score as new data becomes available. The system ingests signals from 13+ independent sources including GitHub, NVD (National Vulnerability Database), OSV.dev, OpenSSF Scorecard, and major package registries (npm, PyPI). When a new CVE is disclosed, a dependency is updated, or commit activity changes, the score adjusts automatically. For the most current score, query the Nerq API: GET nerq.ai/v1/preflight?target=go-playing-agent. The current assessment (76.3/100, B) was last verified on 2026-03-19.
Can I use Go Playing Agent in a regulated environment?
Yes — Go Playing Agent meets the Nerq Verified threshold (70+), indicating it has passed automated trust checks across security, compliance, and maintenance dimensions. Nerq assesses compliance across 52 jurisdictions. Go Playing Agent has a compliance score of 92/100. Under the EU AI Act, Go Playing Agent is classified as minimal risk. For organizations in regulated industries (healthcare, finance, government), we recommend combining the Nerq Trust Score with your internal security review process, vendor risk assessment, and legal compliance check before deployment.

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