Is Learn Agentic Ai Safe?
Learn Agentic Ai — Nerq Trust Score 64.6/100 (C grade). Based on analysis of 5 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-05-04.
Use Learn Agentic Ai with some caution. Learn Agentic Ai is a software tool with a Nerq Trust Score of 64.6/100 (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: 2026-05-04. Machine-readable data (JSON).
Is Learn Agentic Ai safe?
CAUTION — Learn Agentic Ai has a Nerq Trust Score of 64.6/100 (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 Learn Agentic Ai's trust score?
Learn Agentic Ai has a Nerq Trust Score of 64.6/100, 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 Learn Agentic Ai?
Learn Agentic Ai's strongest signal is compliance at 92/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Learn Agentic Ai and who maintains it?
| Author | Tanmay20030516 |
| Category | Coding |
| Source | https://github.com/Tanmay20030516/learn-agentic-ai |
| Frameworks | langchain |
| Protocols | mcp |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 92/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in coding
What Is Learn Agentic Ai?
Learn Agentic Ai is a software tool in the coding category: A coding project for learning Agentic AI using LangChain and LangGraph.. Nerq Trust Score: 65/100 (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 Learn Agentic Ai's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Learn Agentic Ai performs in each:
- Security (0/100): Learn Agentic Ai's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Learn Agentic Ai is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (92/100): Learn Agentic Ai 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 64.6/100 (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 Learn Agentic Ai?
Learn Agentic Ai 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: Learn Agentic Ai 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 Learn Agentic Ai'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 Learn Agentic Ai's dependency tree. - Review permissions — Understand what access Learn Agentic Ai requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Learn Agentic Ai 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=learn-agentic-ai - Review the license — Confirm that Learn Agentic Ai'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 Learn Agentic Ai
When evaluating whether Learn Agentic Ai is safe, consider these category-specific risks:
Understand how Learn Agentic Ai processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Learn Agentic Ai's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Learn Agentic Ai. Security patches and bug fixes are only effective if you're running the latest version.
If Learn Agentic Ai 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 Learn Agentic Ai's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Learn Agentic Ai in violation of its license can expose your organization to legal liability.
Learn Agentic Ai and the EU AI Act
Learn Agentic Ai 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 Learn Agentic Ai Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Learn Agentic Ai while minimizing risk:
Periodically review how Learn Agentic Ai is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Learn Agentic Ai and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Learn Agentic Ai only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Learn Agentic Ai's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Learn Agentic Ai is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Learn Agentic Ai?
Even promising tools aren't right for every situation. Consider avoiding Learn Agentic Ai 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 Learn Agentic Ai's trust score of 64.6/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Learn Agentic Ai 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. Learn Agentic Ai's score of 64.6/100 is above the category average of 62/100.
This positions Learn Agentic Ai 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 Learn Agentic Ai 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, Learn Agentic Ai'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 Learn Agentic Ai's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=learn-agentic-ai&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 Learn Agentic Ai are strengthening or weakening over time.
Learn Agentic Ai vs Alternatives
In the coding category, Learn Agentic Ai scores 64.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Learn Agentic Ai vs AutoGPT — Trust Score: 63.2/100
- Learn Agentic Ai vs ollama — Trust Score: 58.0/100
- Learn Agentic Ai vs langchain — Trust Score: 71.3/100
Key Takeaways
- Learn Agentic Ai has a Trust Score of 64.6/100 (C) and is not yet Nerq Verified.
- Learn Agentic Ai shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among coding tools, Learn Agentic Ai scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 0/100 |
| Maintenance | 1/100 |
| Popularity | 0/100 |
Based on 3 dimensions. Data from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Learn Agentic Ai collect?
Privacy assessment for Learn Agentic Ai is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Learn Agentic Ai secure?
Security score: 0/100. Review security practices and consider alternatives with higher security scores for sensitive use cases.
Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.
Full analysis: Learn Agentic Ai Security Report
How we calculated this score
Learn Agentic Ai's trust score of 64.6/100 (C) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 3 independent dimensions: security (0/100), maintenance (1/100), popularity (0/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on May 04, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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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.