क्या Agent Examples सुरक्षित है?

Agent Examples — Nerq Trust Score 73.8/100 (B ग्रेड). 5 विश्वास आयामों के विश्लेषण के आधार पर, इसे आम तौर पर सुरक्षित लेकिन कुछ चिंताएं हैं माना जाता है। अंतिम अपडेट: 2026-04-04।

हां, Agent Examples उपयोग के लिए सुरक्षित है। Agent Examples एक software tool है Nerq विश्वास स्कोर के साथ 73.8/100 (B), based on 5 स्वतंत्र डेटा आयाम. It is recommended for use. सुरक्षा: 0/100. रखरखाव: 1/100. लोकप्रियता: 0/100. डेटा स्रोत: multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. अंतिम अपडेट: 2026-04-04. मशीन पठनीय डेटा (JSON).

क्या Agent Examples सुरक्षित है?

हां — Agent Examples का Nerq विश्वास स्कोर है 73.8/100 (B). सुरक्षा, रखरखाव और सामुदायिक स्वीकृति में मजबूत संकेतों के साथ Nerq विश्वास सीमा को पूरा करता है. Recommended for use — विशिष्ट विचारों के लिए नीचे पूरी रिपोर्ट देखें.

सुरक्षा विश्लेषण → {name} गोपनीयता रिपोर्ट →

Agent Examples का विश्वास स्कोर क्या है?

Agent Examples का Nerq Trust Score 73.8/100 है, ग्रेड B। यह स्कोर सुरक्षा, रखरखाव और सामुदायिक अपनाने सहित 5 स्वतंत्र रूप से मापे गए आयामों पर आधारित है।

सुरक्षा
0
अनुपालन
92
रखरखाव
1
दस्तावेज़ीकरण
0
लोकप्रियता
0

Agent Examples के प्रमुख सुरक्षा निष्कर्ष क्या हैं?

Agent Examples का सबसे मजबूत संकेत अनुपालन है 92/100 पर। कोई ज्ञात भेद्यता नहीं पाई गई। It meets the Nerq Verified threshold of 70+.

सुरक्षा स्कोर: 0/100 (weak)
रखरखाव: 1/100 — कम रखरखाव गतिविधि
Compliance: 92/100 — covers 47 of 52 jurisdictions
Documentation: 0/100 — सीमित दस्तावेज़ीकरण
लोकप्रियता: 0/100 — 2 स्टार्स github

Agent Examples क्या है और इसका रखरखाव कौन करता है?

डेवलपरkagenti
श्रेणीcoding
स्टार्स2
स्रोतhttps://github.com/kagenti/agent-examples
Protocolsmcp · a2a

नियामक अनुपालन

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

coding में लोकप्रिय विकल्प

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 Agent Examples?

Agent Examples is a software tool in the coding category: Collects examples of community agents and MCP tools.. It has 2 GitHub stars. Nerq Trust Score: 74/100 (B).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including सुरक्षा vulnerabilities, रखरखाव activity, license अनुपालन, and सामुदायिक स्वीकृति.

How Nerq Assesses Agent Examples's Safety

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

The overall Trust Score of 73.8/100 (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 Agent Examples?

Agent Examples is designed for:

Risk guidance: Agent Examples meets the minimum threshold for production use, but we recommend monitoring for सुरक्षा advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.

How to Verify Agent Examples's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — जांचें repository's सुरक्षा policy, open issues, and recent commits for signs of active रखरखाव.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Agent Examples's dependency tree.
  3. समीक्षा permissions — Understand what access Agent Examples requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Agent Examples 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=agent-examples
  6. जांचें license — Confirm that Agent Examples'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 सुरक्षा concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Agent Examples

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

Data handling

Understand how Agent Examples processes, stores, and transmits your data. जांचें tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency सुरक्षा

Check Agent Examples's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher सुरक्षा risk.

Update frequency

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

Third-party integrations

If Agent Examples 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 अनुपालन

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

Agent Examples and the EU AI Act

Agent Examples 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 अनुपालन assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal अनुपालन.

Best Practices for Using Agent Examples Safely

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

Conduct regular audits

Periodically review how Agent Examples is used in your workflow. Check for unexpected behavior, permissions drift, and अनुपालन with your सुरक्षा policies.

Keep dependencies updated

Ensure Agent Examples and all its dependencies are running the latest stable versions to benefit from सुरक्षा patches.

Follow least privilege

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

Monitor for सुरक्षा advisories

Subscribe to Agent Examples's सुरक्षा 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 Agent Examples is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Agent Examples?

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

For each scenario, evaluate whether Agent Examples का विश्वास स्कोर 73.8/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.

How Agent Examples 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. Agent Examples's score of 73.8/100 is significantly above the category average of 62/100.

This places Agent Examples in the top tier of coding tools that Nerq tracks. Tools scoring this far above average typically demonstrate mature सुरक्षा practices, consistent release cadence, and broad सामुदायिक स्वीकृति.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks मध्यम 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 Agent Examples 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 रखरखाव patterns change, Agent Examples'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 सुरक्षा and quality. Conversely, a downward trend may signal reduced रखरखाव, growing technical debt, or unresolved vulnerabilities. To track Agent Examples's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=agent-examples&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 — सुरक्षा, रखरखाव, दस्तावेज़ीकरण, अनुपालन, and community — has evolved independently, providing granular visibility into which aspects of Agent Examples are strengthening or weakening over time.

Agent Examples vs विकल्प

coding श्रेणी में, Agent Examples का स्कोर 73.8/100 है। There are higher-scoring alternatives available. For a detailed comparison, see:

मुख्य निष्कर्ष

अक्सर पूछे जाने वाले प्रश्न

क्या Agent Examples उपयोग के लिए सुरक्षित है?
हां, यह उपयोग के लिए सुरक्षित है। agent-examples का Nerq विश्वास स्कोर है 73.8/100 (B). सबसे मजबूत संकेत: अनुपालन (92/100). स्कोर आधारित सुरक्षा (0/100), रखरखाव (1/100), लोकप्रियता (0/100), दस्तावेज़ीकरण (0/100).
Agent Examples's trust score क्या है?
agent-examples: 73.8/100 (B). स्कोर आधारित: सुरक्षा (0/100), रखरखाव (1/100), लोकप्रियता (0/100), दस्तावेज़ीकरण (0/100). Compliance: 92/100. नया डेटा उपलब्ध होने पर स्कोर अपडेट होते हैं। API: GET nerq.ai/v1/preflight?target=agent-examples
Agent Examples के अधिक सुरक्षित विकल्प क्या हैं?
coding श्रेणी में, उच्च-रेटेड विकल्पों में शामिल हैं: Significant-Gravitas/AutoGPT (75/100), ollama/ollama (74/100), langchain-ai/langchain (86/100). agent-examples का स्कोर 73.8/100 है।
How often is Agent Examples's safety score updated?
Nerq continuously monitors Agent Examples and updates its trust score as new data becomes available. डेटा स्रोत: multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Current: 73.8/100 (B), last सत्यापित 2026-04-04. API: GET nerq.ai/v1/preflight?target=agent-examples
क्या मैं Agent Examples को विनियमित वातावरण में उपयोग कर सकता हूं?
Yes — Agent Examples meets the Nerq Verified threshold (70+). Combine this with your internal सुरक्षा review for regulated deployments.
API: /v1/preflight Trust Badge API Docs

Disclaimer: Nerq विश्वास स्कोर सार्वजनिक रूप से उपलब्ध संकेतों पर आधारित स्वचालित मूल्यांकन हैं। ये सिफारिश या गारंटी नहीं हैं। हमेशा अपना स्वयं का सत्यापन करें।

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