Is Agentclaw Safe?
Agentclaw — Nerq Trust Score 55.8/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Agentclaw is a Python package with a Nerq Trust Score of 55.8/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 15/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Agentclaw safe?
Trust Score Breakdown — Agentclaw has a Nerq Trust Score of 55.8/100 (C). Measured across 2 independent trust signals (as of 2026-03-20).
What is Agentclaw's trust score?
Agentclaw has a Nerq Trust Score of 55.8/100, earning a C grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Agentclaw?
Agentclaw's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Agentclaw and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Agentclaw
What is Agentclaw?
Agentclaw is a Python package — Visual debugger for AI agents. See every step, every decision, every failure..
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=agentclaw
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Agentclaw has a Nerq Trust Score of 56/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Agentclaw has a Trust Score of 56/100 (C).
- The score is a measured composite — it is not a suitability judgment. Evaluate the individual signals against your own requirements.
- Query the current measured values via the Nerq API.
Frequently Asked Questions
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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.