Apakah Coding Agent Eval Aman?

Coding Agent Eval — Nerq Trust Score 62.4/100 (Nilai C). Berdasarkan analisis 5 dimensi kepercayaan, dianggap umumnya aman tetapi memiliki beberapa kekhawatiran. Terakhir diperbarui: 2026-04-01.

Gunakan Coding Agent Eval dengan hati-hati. Coding Agent Eval is a software tool dengan Skor Kepercayaan Nerq sebesar 62.4/100 (C), based on 5 independent data dimensions. Di bawah ambang batas yang direkomendasikan yaitu 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: 2026-04-01. Data yang dapat dibaca mesin (JSON).

Apakah Coding Agent Eval Aman?

HATI-HATI — Coding Agent Eval memiliki Skor Kepercayaan Nerq sebesar 62.4/100 (C). Memiliki sinyal kepercayaan sedang tetapi menunjukkan beberapa area yang perlu diperhatikan. Cocok untuk penggunaan pengembangan — tinjau sinyal keamanan dan pemeliharaan sebelum penerapan produksi.

Analisis Keamanan → Laporan Privasi {name} →

Berapa skor kepercayaan Coding Agent Eval?

Coding Agent Eval memiliki Skor Kepercayaan Nerq 62.4/100 dengan nilai C. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.

Keamanan
0
Kepatuhan
100
Pemeliharaan
1
Dokumentasi
0
Popularitas
0

Apa temuan keamanan utama untuk Coding Agent Eval?

Sinyal terkuat Coding Agent Eval adalah kepatuhan pada 100/100. Tidak ada kerentanan yang diketahui terdeteksi. Belum mencapai ambang verifikasi Nerq 70+.

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

Apa itu Coding Agent Eval dan siapa yang mengelolanya?

PembuatJack-Kin
Kategoricoding
Sumberhttps://github.com/Jack-Kin/coding-agent-eval
Frameworksanthropic

Kepatuhan Regulasi

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

Alternatif Populer di coding

Significant-Gravitas/AutoGPT
74.7/100 · B
github
ollama/ollama
73.8/100 · B
github
langchain-ai/langchain
86.4/100 · A
github
x1xhlol/system-prompts-and-models-of-ai-tools
73.8/100 · B
github
anomalyco/opencode
87.9/100 · A
github

What Is Coding Agent Eval?

Coding Agent Eval is a software tool in the coding category: A Python harness for benchmarking coding agents on realistic software tasks.. Nerq Trust Score: 62/100 (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 Coding Agent Eval's Safety

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

The overall Trust Score of 62.4/100 (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 Coding Agent Eval?

Coding Agent Eval is designed for:

Risk guidance: Coding Agent Eval 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 Coding Agent Eval'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 Coding Agent Eval's dependency tree.
  3. Ulasan permissions — Understand what access Coding Agent Eval requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Coding Agent Eval 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=coding-agent-eval
  6. Tinjau license — Confirm that Coding Agent Eval'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 Coding Agent Eval

When evaluating whether Coding Agent Eval is safe, consider these category-specific risks:

Data handling

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

Update frequency

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

Third-party integrations

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

Coding Agent Eval and the EU AI Act

Coding Agent Eval 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 Coding Agent Eval Safely

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

Conduct regular audits

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

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

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

When Should You Avoid Coding Agent Eval?

Even promising tools aren't right for every situation. Consider avoiding Coding Agent Eval in these scenarios:

Skor kepercayaan

For each scenario, evaluate whether Coding Agent Eval sebesar 62.4/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Coding Agent Eval 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. Coding Agent Eval's score of 62.4/100 is above the category average of 62/100.

This positions Coding Agent Eval favorably among coding 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 Coding Agent Eval 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, Coding Agent Eval'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 Coding Agent Eval's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=coding-agent-eval&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 Coding Agent Eval are strengthening or weakening over time.

Coding Agent Eval vs Alternatives

Dalam kategori coding, Coding Agent Eval mendapat skor 62.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kesimpulan Utama

Pertanyaan yang Sering Diajukan

Apakah Coding Agent Eval aman digunakan?
Gunakan dengan hati-hati. coding-agent-eval memiliki Skor Kepercayaan Nerq sebesar 62.4/100 (C). Sinyal terkuat: kepatuhan (100/100). Skor berdasarkan security (0/100), maintenance (1/100), popularity (0/100), documentation (0/100).
Berapa skor kepercayaan Coding Agent Eval?
coding-agent-eval: 62.4/100 (C). Skor berdasarkan: security (0/100), maintenance (1/100), popularity (0/100), documentation (0/100). Compliance: 100/100. Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=coding-agent-eval
Apa alternatif yang lebih aman dari Coding Agent Eval?
Dalam kategori coding, alternatif berperingkat lebih tinggi termasuk Significant-Gravitas/AutoGPT (75/100), ollama/ollama (74/100), langchain-ai/langchain (86/100). coding-agent-eval mendapat skor 62.4/100.
How often is Coding Agent Eval's safety score updated?
Nerq continuously monitors Coding Agent Eval 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: 62.4/100 (C), last verified 2026-04-01. API: GET nerq.ai/v1/preflight?target=coding-agent-eval
Bisakah saya menggunakan Coding Agent Eval di lingkungan teregulasi?
Coding Agent Eval has not reached the Nerq Verified threshold of 70. Additional due diligence is recommended for regulated environments.
API: /v1/preflight Trust Badge API Docs

Disclaimer: Skor kepercayaan Nerq adalah penilaian otomatis berdasarkan sinyal yang tersedia secara publik. Ini bukan rekomendasi atau jaminan. Selalu lakukan verifikasi mandiri Anda sendiri.

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