Is Opencode Agent Conversations Safe?
Opencode Agent Conversations — Nerq Trust Score 64.5/100 (C grade). Score based on 5 independent trust signals.
Opencode Agent Conversations is a software tool with a Nerq Trust Score of 64.5/100 (C), based on 5 independent data dimensions. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: n/a. Machine-readable data (JSON).
Is Opencode Agent Conversations safe?
Trust Score Breakdown — Opencode Agent Conversations has a Nerq Trust Score of 64.5/100 (C). Measured across 5 independent trust signals.
What is Opencode Agent Conversations's trust score?
Opencode Agent Conversations has a Nerq Trust Score of 64.5/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Opencode Agent Conversations?
Opencode Agent Conversations's strongest signal is compliance at 100/100. No known vulnerabilities have been detected.
What is Opencode Agent Conversations and who maintains it?
| Author | marcel-tuinstra |
| Category | Communication |
| Stars | 2 |
| Source | https://github.com/marcel-tuinstra/opencode-agent-conversations |
| Protocols | mcp |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in communication
What Is Opencode Agent Conversations?
Opencode Agent Conversations is a software tool in the communication category: Community plugin for OpenCode to run and orchestrate multi-agent conversations.. It has 2 GitHub stars. Nerq Trust Score: 64/100 (C).
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 Opencode Agent Conversations's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Opencode Agent Conversations performs in each:
- Security (0/100): Opencode Agent Conversations's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Opencode Agent Conversations 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 (100/100): Opencode Agent Conversations is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 64.5/100 (C) is the weighted combination of these measured signals. It is a measurement, not a pass/fail or suitability judgment — weigh the individual signals against your own requirements.
Who Typically Evaluates Opencode Agent Conversations?
Opencode Agent Conversations is commonly evaluated by:
- Developers and teams working with communication tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Opencode Agent Conversations's measured signals (security 0/100, maintenance 1/100, documentation 1/100, community 0/100) are shown above. These are measurements, not a suitability judgment — weigh each signal against the requirements of your own use case and risk tolerance.
How to Verify Opencode Agent Conversations's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository's security 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 Opencode Agent Conversations's dependency tree. - Review permissions — Understand what access Opencode Agent Conversations requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Opencode Agent Conversations 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-agent-conversations - Review the license — Confirm that Opencode Agent Conversations'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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Opencode Agent Conversations
When evaluating whether Opencode Agent Conversations is safe, consider these category-specific risks:
Understand how Opencode Agent Conversations processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Opencode Agent Conversations's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Opencode Agent Conversations. Security patches and bug fixes are only effective if you're running the latest version.
If Opencode Agent Conversations 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 Agent Conversations'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 Agent Conversations in violation of its license can expose your organization to legal liability.
Opencode Agent Conversations and the EU AI Act
Opencode Agent Conversations 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 Opencode Agent Conversations Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Opencode Agent Conversations while minimizing risk:
Periodically review how Opencode Agent Conversations is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Opencode Agent Conversations and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Opencode Agent Conversations only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Opencode Agent Conversations's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Opencode Agent Conversations is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Opencode Agent Conversations
Nerq's signals are one input. In the following situations, evaluate Opencode Agent Conversations's measured signals against your own requirements before making a decision:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
For each situation, compare Opencode Agent Conversations's measured trust score of 64.5/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Opencode Agent Conversations is suitable for any particular use.
How Opencode Agent Conversations Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among communication tools, the average Trust Score is 62/100. Opencode Agent Conversations's score of 64.5/100 is above the category average of 62/100.
This positions Opencode Agent Conversations favorably among communication 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 Opencode Agent Conversations 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, Opencode Agent Conversations'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 Opencode Agent Conversations's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=opencode-agent-conversations&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 Opencode Agent Conversations are strengthening or weakening over time.
Opencode Agent Conversations vs Alternatives
In the communication category, Opencode Agent Conversations scores 64.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Opencode Agent Conversations vs ChatGPT — Trust Score: 59.4/100
- Opencode Agent Conversations vs jan — Trust Score: 64.4/100
- Opencode Agent Conversations vs ChatTTS — Trust Score: 55.0/100
Key Takeaways
- Opencode Agent Conversations has a measured Nerq Trust Score of 64.5/100 (C) — a composite of independent signals, not a suitability judgment.
- Among communication tools, Opencode Agent Conversations scores above the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — security, maintenance, documentation, compliance, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Frequently Asked Questions
Is Opencode Agent Conversations Safe?
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See Also
Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.