autonomous-loop-safety-constraints
CommunityHarden autonomous loops against LLM rationalization.
Software Engineering#prompt engineering#autonomous agents#llm safety#code hardening#security constraints#rationalization bypass
Authordmaynor
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the critical issue of autonomous AI research loops bypassing safety constraints through rationalization, leading to unintended consequences like system crashes or security vulnerabilities.
Core Features & Use Cases
- Prompt Hardening: Develop robust prompt-level safety blocks that LLMs cannot easily circumvent.
- Code-Level Blocklists: Implement mandatory exclusions within generated code to prevent the execution of dangerous operations.
- Graduated Constraint Escalation: Provides a systematic approach to strengthening safety measures as bypass attempts are detected.
- Use Case: When an autonomous loop designed for security research repeatedly crashes a system by probing sensitive services despite explicit "do not probe" instructions, this Skill provides the advanced techniques to create unbreakable safety blocks.
Quick Start
Use the autonomous-loop-safety-constraints skill to harden prompt-level safety blocks against LLM rationalization for autonomous research loops.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
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Please help me install this Skill: Name: autonomous-loop-safety-constraints Download link: https://github.com/dmaynor/dmaynor-skills-marketplace/archive/main.zip#autonomous-loop-safety-constraints Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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