Is Langgraph Personal Coworker Safe?
Langgraph Personal Coworker — Nerq Trust Score 49.1/100 (D grade). Score based on 5 independent trust signals.
Langgraph Personal Coworker is a software tool with a Nerq Trust Score of 49.1/100 (D), based on 5 independent data dimensions. 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: n/a. Machine-readable data (JSON).
Is Langgraph Personal Coworker safe?
Trust Score Breakdown — Langgraph Personal Coworker has a Nerq Trust Score of 49.1/100 (D). Measured across 5 independent trust signals.
What is Langgraph Personal Coworker's trust score?
Langgraph Personal Coworker has a Nerq Trust Score of 49.1/100, earning a D grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Langgraph Personal Coworker?
Langgraph Personal Coworker's strongest signal is compliance at 87/100. No known vulnerabilities have been detected.
What is Langgraph Personal Coworker and who maintains it?
| Author | oeilsimple |
| Category | Research |
| Source | https://github.com/oeilsimple/langgraph-personal-coworker |
| Frameworks | openai |
| Protocols | rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 87/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in research
What Is Langgraph Personal Coworker?
Langgraph Personal Coworker is a software tool in the research category: Sidekick is an intelligent multi-agent research assistant that combines the power of LangGraph and Gradio to deliver reliable, up-to-date answers.. Nerq Trust Score: 49/100 (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 Langgraph Personal Coworker's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Langgraph Personal Coworker performs in each:
- Security (0/100): Langgraph Personal Coworker's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Langgraph Personal Coworker is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (87/100): Langgraph Personal Coworker 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 49.1/100 (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 Langgraph Personal Coworker?
Langgraph Personal Coworker is commonly evaluated by:
- Developers and teams working with research tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Langgraph Personal Coworker's measured signals (security 0/100, maintenance 1/100, documentation 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 Langgraph Personal Coworker'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 Langgraph Personal Coworker's dependency tree. - Review permissions — Understand what access Langgraph Personal Coworker requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Langgraph Personal Coworker 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=langgraph-personal-coworker - Review the license — Confirm that Langgraph Personal Coworker'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 Langgraph Personal Coworker
When evaluating whether Langgraph Personal Coworker is safe, consider these category-specific risks:
Understand how Langgraph Personal Coworker processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Langgraph Personal Coworker's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Langgraph Personal Coworker. Security patches and bug fixes are only effective if you're running the latest version.
If Langgraph Personal Coworker 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 Langgraph Personal Coworker's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Langgraph Personal Coworker in violation of its license can expose your organization to legal liability.
Langgraph Personal Coworker and the EU AI Act
Langgraph Personal Coworker 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 Langgraph Personal Coworker Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Langgraph Personal Coworker while minimizing risk:
Periodically review how Langgraph Personal Coworker is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Langgraph Personal Coworker and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Langgraph Personal Coworker only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Langgraph Personal Coworker's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Langgraph Personal Coworker is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Langgraph Personal Coworker
Nerq's signals are one input. In the following situations, evaluate Langgraph Personal Coworker's measured signals against your own requirements before making a decision:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
For each situation, compare Langgraph Personal Coworker's measured trust score of 49.1/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Langgraph Personal Coworker is suitable for any particular use.
How Langgraph Personal Coworker Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among research tools, the average Trust Score is 62/100. Langgraph Personal Coworker's score of 49.1/100 is below the category average of 62/100.
This suggests that Langgraph Personal Coworker trails behind many comparable research 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 Langgraph Personal Coworker 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, Langgraph Personal Coworker'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 Langgraph Personal Coworker's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=langgraph-personal-coworker&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 Langgraph Personal Coworker are strengthening or weakening over time.
Langgraph Personal Coworker vs Alternatives
In the research category, Langgraph Personal Coworker scores 49.1/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Langgraph Personal Coworker vs gpt_academic — Trust Score: 60.9/100
- Langgraph Personal Coworker vs LlamaFactory — Trust Score: 83.7/100
- Langgraph Personal Coworker vs unsloth — Trust Score: 77.2/100
Key Takeaways
- Langgraph Personal Coworker has a measured Nerq Trust Score of 49.1/100 (D) — a composite of independent signals, not a suitability judgment.
- Among research tools, Langgraph Personal Coworker scores below the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — security, maintenance, documentation, compliance, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Frequently Asked Questions
Is Langgraph Personal Coworker Safe?
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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.