Is Fellowship Code Safe?
Fellowship Code — Nerq Trust Score 56.2/100 (C grade). Based on analysis of 5 trust dimensions, it is has notable safety concerns. Last updated: 2026-07-11.
Use Fellowship Code with some caution. Fellowship Code is a software tool with a Nerq Trust Score of 56.2/100 (C), based on 5 independent data dimensions. Below the recommended threshold of 70. 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: 2026-07-11. Machine-readable data (JSON).
Is Fellowship Code safe?
CAUTION — Fellowship Code has a Nerq Trust Score of 56.2/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
What is Fellowship Code's trust score?
Fellowship Code has a Nerq Trust Score of 56.2/100, 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 Fellowship Code?
Fellowship Code's strongest signal is compliance at 100/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Fellowship Code and who maintains it?
| Author | endaoment |
| Category | Coding |
| Source | https://github.com/endaoment/fellowship-code |
| Frameworks | anthropic |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in coding
What Is Fellowship Code?
Fellowship Code is a software tool in the coding category: An open-source multi-agent AI engineering team for Cursor and Claude Code.. Nerq Trust Score: 56/100 (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 Fellowship Code's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Fellowship Code performs in each:
- Security (0/100): Fellowship Code's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Fellowship Code 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): Fellowship Code 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 56.2/100 (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 Fellowship Code?
Fellowship Code 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: Fellowship Code is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Fellowship Code'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 Fellowship Code's dependency tree. - Review permissions — Understand what access Fellowship Code requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Fellowship Code 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=fellowship-code - Review the license — Confirm that Fellowship Code'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 Fellowship Code
When evaluating whether Fellowship Code is safe, consider these category-specific risks:
Understand how Fellowship Code processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Fellowship Code's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Fellowship Code. Security patches and bug fixes are only effective if you're running the latest version.
If Fellowship Code 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 Fellowship Code's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Fellowship Code in violation of its license can expose your organization to legal liability.
Fellowship Code and the EU AI Act
Fellowship Code 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 Fellowship Code Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Fellowship Code while minimizing risk:
Periodically review how Fellowship Code is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Fellowship Code and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Fellowship Code only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Fellowship Code's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Fellowship Code is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Fellowship Code?
Even promising tools aren't right for every situation. Consider avoiding Fellowship Code in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Fellowship Code's trust score of 56.2/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Fellowship Code Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Fellowship Code's score of 56.2/100 is near the category average of 62/100.
This places Fellowship Code in line with the typical coding tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.
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 Fellowship Code 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, Fellowship Code'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 Fellowship Code's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=fellowship-code&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 Fellowship Code are strengthening or weakening over time.
Fellowship Code vs Alternatives
In the coding category, Fellowship Code scores 56.2/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Fellowship Code vs AutoGPT — Trust Score: 61.8/100
- Fellowship Code vs ollama — Trust Score: 56.5/100
- Fellowship Code vs langchain — Trust Score: 69.8/100
Key Takeaways
- Fellowship Code has a Trust Score of 56.2/100 (C) and is not yet Nerq Verified.
- Fellowship Code shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Fellowship Code scores near the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Frequently Asked Questions
Is Fellowship Code Safe?
What is Fellowship Code's trust score?
What are safer alternatives to Fellowship Code?
How often is Fellowship Code's safety score updated?
Can I use Fellowship Code in a regulated environment?
See Also
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.