Is Agentcourt Safe?

Agentcourt — Nerq Trust Score 53.0/100 (D grade). Score based on 4 independent trust signals.

Agentcourt is a software tool with a Nerq Trust Score of 53.0/100 (D), based on 4 independent data dimensions. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: n/a. Machine-readable data (JSON).

Is Agentcourt safe?

Trust Score Breakdown — Agentcourt has a Nerq Trust Score of 53.0/100 (D). Measured across 4 independent trust signals.

Security Analysis → Agentcourt Privacy Report →

What is Agentcourt's trust score?

Agentcourt has a Nerq Trust Score of 53.0/100, earning a D grade. This score is based on 4 independently measured dimensions including security, maintenance, and community adoption.

Compliance
84
Maintenance
0
Documentation
0
Popularity
0

What are the key security findings for Agentcourt?

Agentcourt's strongest signal is compliance at 84/100. No known vulnerabilities have been detected.

Maintenance: 0/100 — low maintenance activity
Compliance: 84/100 — covers 43 of 52 jurisdictions
Documentation: 0/100 — limited documentation
Popularity: 0/100 — 3 stars on huggingface dataset full

What is Agentcourt and who maintains it?

Authoryouzi517
CategoryLegal
Stars3
Sourcehttps://huggingface.co/datasets/youzi517/AgentCourt
Protocolshuggingface_hub

Regulatory Compliance

EU AI Act Risk ClassNot assessed
Compliance Score84/100
JurisdictionsAssessed across 52 jurisdictions

Popular Alternatives in legal

Deodat-Lawson/PDR_AI_v2
60.4/100 · C
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Ramseygithub/ai-legal-compliance-assistant
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lawglance/lawglance
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huggingface_search_ext

What Is Agentcourt?

Agentcourt is a software tool in the legal category: Automated legal assistant for case analysis and research.. It has 3 GitHub stars. Nerq Trust Score: 53/100 (D).

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 Agentcourt's Safety

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

The overall Trust Score of 53.0/100 (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 Agentcourt?

Agentcourt is commonly evaluated by:

How to read the signals: Agentcourt's measured signals (maintenance 0/100, documentation 0/100, 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 Agentcourt'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 Agentcourt's dependency tree.
  3. Review permissions — Understand what access Agentcourt requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Agentcourt 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=AgentCourt
  6. Review the license — Confirm that Agentcourt'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 Agentcourt

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

Data handling

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

Update frequency

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

Third-party integrations

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

Best Practices for Using Agentcourt Safely

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

Conduct regular audits

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

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

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

Situations That Warrant Independent Review of Agentcourt

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

For each situation, compare Agentcourt's measured trust score of 53.0/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Agentcourt is suitable for any particular use.

How Agentcourt Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among legal tools, the average Trust Score is 62/100. Agentcourt's score of 53.0/100 is near the category average of 62/100.

This places Agentcourt in line with the typical legal tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

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 Agentcourt 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, Agentcourt'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 Agentcourt's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=AgentCourt&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 Agentcourt are strengthening or weakening over time.

Agentcourt vs Alternatives

In the legal category, Agentcourt scores 53.0/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Key Takeaways

Frequently Asked Questions

Is Agentcourt Safe?
AgentCourt with a Nerq Trust Score of 53.0/100 (D). Strongest signal: compliance (84/100). Score based on Maintenance (0/100), Popularity (0/100), Documentation (0/100).
What is Agentcourt's trust score?
AgentCourt: 53.0/100 (D). Score based on Maintenance (0/100), Popularity (0/100), Documentation (0/100). Compliance: 84/100. Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=AgentCourt
What are safer alternatives to Agentcourt?
In the Legal category, higher-rated alternatives include Deodat-Lawson/PDR_AI_v2 (60/100), Ramseygithub/ai-legal-compliance-assistant (56/100), lawglance/lawglance (58/100). AgentCourt scores 53.0/100.
How often is Agentcourt's safety score updated?
Nerq recomputes Agentcourt's trust score as new data becomes available. Current: 53.0/100 (D). API: GET nerq.ai/v1/preflight?target=AgentCourt
Can I use Agentcourt in a regulated environment?
Agentcourt: 53.0/100 (D). Compliance: 43 of 52 jurisdictions. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

See Also

Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.

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