hybridclaw
Reduces security risk and compliance overhead by enabling AI-assisted development within controlled infrastructure boundaries, with built-in credential isola…
Enterprise-ready self-hosted AI assistant runtime with sandboxed execution, secure credentials, approvals, and memory
- Ask Claude to execute code scripts safely within sandboxed environments for testing
- Generate automated workflows that require approval gates before running sensitive operations
- Find and retrieve stored credentials securely without exposing them in logs or outputs
Reduces security risk and compliance overhead by enabling AI-assisted development within controlled infrastructure boundaries, with built-in credential isolation and approval workflows that satisfy enterprise governance requirements.
Enterprise engineering teams requiring self-hosted AI coding assistance with audit trails and credential management for regulated environments.
https://github.com/HybridAIOne/hybridclaw
By HybridAIOne
How to Get It
claude plugins install HybridAIOne/hybridclaw
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Execute code scripts safely within sandboxed environments for testing
Trust Signals Auto-scanned
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 159 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 159 GitHub stars; contributors unknown; last commit 0d ago; license MIT.