Je Dakeai bezpečný?

Je Dakeai bezpečný?

NE — POUŽÍVEJTE S OPATRNOSTÍ — Dakeai má skóre důvěryhodnosti Nerq 40.7/100 (E). Má podprůměrné signály důvěryhodnosti s významnými mezerami v bezpečnosti, údržbě nebo dokumentaci. Nedoporučeno pro produkční použití bez důkladné ruční kontroly a dalších bezpečnostních opatření.

What Is Dakeai?

Dakeai is a software tool in the ai category: dakeai is an AI assistant.. Nerq Trust Score: 41/100 (E).

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 Dakeai's Safety

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

• Údržba (0/100): Dakeai 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.
• Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.

The overall Trust Score of 40.7/100 (E) 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 Dakeai?

Dakeai is designed for:

• Developers and teams working with ai tools
• Organizations evaluating AI tools for their stack
• Researchers exploring AI capabilities in this domain

Risk guidance: We recommend caution with Dakeai. The low trust score suggests potential risks in security, maintenance, or community support. Consider using a more established alternative for any production or sensitive workload.

How to Verify Dakeai'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 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 Dakeai's dependency tree.
3. Recenze permissions — Understand what access Dakeai requires. Software tools should follow the principle of least privilege.
4. Test in isolation — Run Dakeai 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=dakeai
6. Zkontrolujte license — Confirm that Dakeai'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 Dakeai

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

Best Practices for Using Dakeai Safely

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

When Should You Avoid Dakeai?

Even promising tools aren't right for every situation. Consider avoiding Dakeai 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 Dakeai 40.7/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Dakeai Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among ai tools, the average Trust Score is 62/100. Dakeai's score of 40.7/100 is below the category average of 62/100.

This suggests that Dakeai trails behind many comparable ai tools. Organizations with strict security 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 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 Dakeai 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, Dakeai'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 Dakeai's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=dakeai&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 Dakeai are strengthening or weakening over time.

Dakeai vs Alternatives

V kategorii ai, Dakeai získal skóre 40.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:

• Dakeai vs Arize Phoenix — Trust Score: 50.7/100
• Dakeai vs Hermes-3-Llama-3.2-3B — Trust Score: 60.1/100
• Dakeai vs AlphaMaze-v0.2-1.5B — Trust Score: 59.2/100

Hlavní závěry

• Dakeai má skóre důvěryhodnosti 40.7/100 (E) and is not yet Nerq Verified.
• Dakeai has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
• Among ai tools, Dakeai scores below 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.