Apakah Multi Agentic Planners Aman?

Multi Agentic Planners — Nerq Trust Score 50.8/100 (Nilai D). Skor berdasarkan 5 independent trust signals.

Multi Agentic Planners adalah software tool dengan Skor Kepercayaan Nerq sebesar 50.8/100 (D), based on 5 dimensi data independen. Keamanan: 0/100. Pemeliharaan: 1/100. Popularitas: 0/100. Data bersumber dari berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard. Terakhir diperbarui: n/a. Data yang dapat dibaca mesin (JSON).

Apakah Multi Agentic Planners Aman?

Rincian Skor Kepercayaan — Multi Agentic Planners has a Nerq Trust Score of 50.8/100 (D). Measured across 5 independent trust signals.

Analisis Keamanan → Laporan Privasi Multi Agentic Planners →

Berapa skor kepercayaan Multi Agentic Planners?

Multi Agentic Planners memiliki Skor Kepercayaan Nerq 50.8/100 dengan nilai D. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.

Keamanan
0
Kepatuhan
100
Pemeliharaan
1
Dokumentasi
1
Popularitas
0

Apa temuan keamanan utama untuk Multi Agentic Planners?

Sinyal terkuat Multi Agentic Planners adalah kepatuhan pada 100/100. Tidak ada kerentanan yang diketahui terdeteksi.

⚠Skor keamanan: 0/100 (lemah)
⚠Pemeliharaan: 1/100 — aktivitas pemeliharaan rendah
⚠Kepatuhan: 100/100 — covers 52 of 52 jurisdictions
⚠Dokumentasi: 1/100 — dokumentasi terbatas
⚠Popularitas: 0/100 — adopsi komunitas

Apa itu Multi Agentic Planners dan siapa yang mengelolanya?

PembuatBhargavi-hash
KategoriDevops
Sumberhttps://github.com/Bhargavi-hash/Multi-Agentic-Planners
Frameworksopenai
Protocolsrest

Kepatuhan Regulasi

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

Alternatif Populer di devops

ansible/ansible
74.9/100 · B
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FlowiseAI/Flowise
67.5/100 · C
github
shareAI-lab/learn-claude-code
72.1/100 · B
github
continuedev/continue
75.0/100 · B
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wshobson/agents
79.3/100 · B
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What Is Multi Agentic Planners?

Multi Agentic Planners is a DevOps tool: A lightweight planning-based agent for managing GitHub repositories via natural language prompts.. Nerq Trust Score: 51/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including keamanan vulnerabilities, pemeliharaan activity, license kepatuhan, and adopsi komunitas.

How Nerq Assesses Multi Agentic Planners's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensi. Here is how Multi Agentic Planners performs in each:

The overall Trust Score of 50.8/100 (D) 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 Multi Agentic Planners?

Multi Agentic Planners is commonly evaluated by:

How to read the signals: Multi Agentic Planners's measured signals (keamanan 0/100, pemeliharaan 1/100, dokumentasi 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 Multi Agentic Planners's Safety Yourself

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

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

Common Safety Concerns with Multi Agentic Planners

When evaluating whether Multi Agentic Planners is safe, consider these category-specific risks:

Data handling

Understand how Multi Agentic Planners processes, stores, and transmits your data. Tinjau tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency keamanan

Check Multi Agentic Planners's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher keamanan risk.

Update frequency

Regularly check for updates to Multi Agentic Planners. Keamanan patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Multi Agentic Planners 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 kepatuhan

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

Multi Agentic Planners and the EU AI Act

Multi Agentic Planners 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 kepatuhan assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal kepatuhan.

Best Practices for Using Multi Agentic Planners Safely

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

Conduct regular audits

Periodically review how Multi Agentic Planners is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.

Keep dependencies updated

Ensure Multi Agentic Planners and all its dependencies are running the latest stable versions to benefit from keamanan patches.

Follow least privilege

Grant Multi Agentic Planners only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for keamanan advisories

Subscribe to Multi Agentic Planners's keamanan 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 Multi Agentic Planners is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Multi Agentic Planners

Nerq's signals are one input. In the following situations, evaluate Multi Agentic Planners's measured signals against your own requirements before making a decision:

For each situation, compare Multi Agentic Planners's measured trust score of 50.8/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Multi Agentic Planners is suitable for any particular use.

How Multi Agentic Planners Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among DevOps tools, the average Trust Score is 63/100. Multi Agentic Planners's score of 50.8/100 is below the category average of 63/100.

This suggests that Multi Agentic Planners trails behind many comparable DevOps tools. Organizations with strict keamanan requirements should evaluate whether higher-scoring alternatives better meet their needs.

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

Multi Agentic Planners vs Alternatif

In the devops category, Multi Agentic Planners scores 50.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kesimpulan Utama

Pertanyaan yang Sering Diajukan

Apakah Multi Agentic Planners Aman?
Multi-Agentic-Planners dengan Skor Kepercayaan Nerq sebesar 50.8/100 (D). Sinyal terkuat: kepatuhan (100/100). Skor berdasarkan Keamanan (0/100), Pemeliharaan (1/100), Popularitas (0/100), Dokumentasi (1/100).
Berapa skor kepercayaan Multi Agentic Planners?
Multi-Agentic-Planners: 50.8/100 (D). Skor berdasarkan Keamanan (0/100), Pemeliharaan (1/100), Popularitas (0/100), Dokumentasi (1/100). Compliance: 100/100. Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=Multi-Agentic-Planners
Apa alternatif yang lebih aman dari Multi Agentic Planners?
Dalam kategori Devops, higher-rated alternatives include ansible/ansible (75/100), FlowiseAI/Flowise (68/100), shareAI-lab/learn-claude-code (72/100). Multi-Agentic-Planners scores 50.8/100.
Seberapa sering skor keamanan Multi Agentic Planners diperbarui?
Nerq recomputes Multi Agentic Planners's trust score as new data becomes available. Current: 50.8/100 (D). API: GET nerq.ai/v1/preflight?target=Multi-Agentic-Planners
Bisakah saya menggunakan Multi Agentic Planners di lingkungan yang diatur?
Multi Agentic Planners: 50.8/100 (D). Compliance: 52 of 52 jurisdictions. EU AI Act compliant. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Lihat juga

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