✅ COMPREHENSIVE SAFETY FRAMEWORK:
• Package-level safety notices with SACRED TRUST language
• Server-level LLM safety protocols with specific refusal scenarios
• Class-level safety reminders for AI assistants
• Tool-level destructive operation warnings (🔴 DESTRUCTIVE markers)
• Visual safety system: 🔴🛡️🚨 markers throughout codebase
• Emergency logging infrastructure with proper escalation
• Default-safe operations (dry_run=True for destructive tools)
🔒 DESTRUCTIVE OPERATION PROTECTIONS:
• bulk_rename: LLM safety instructions + dry_run default
• search_and_replace_batch: Comprehensive safety warnings
• All destructive tools require preview before execution
• Clear REFUSE scenarios for AI assistants
📚 COMPREHENSIVE DOCUMENTATION:
• SACRED_TRUST_SAFETY.md: Complete safety philosophy & implementation guide
• IMPLEMENTATION_COMPLETE.md: Project completion status
• EMERGENCY_LOGGING_COMPLETE.md: Logging infrastructure details
• UV_BUILD_GUIDE.md: Modern Python project setup
• Multiple implementation guides and status docs
🔧 PROJECT MODERNIZATION:
• Migrated from setup.py/requirements.txt to pyproject.toml + uv
• Updated dependency management with uv.lock
• Enhanced test suite with comprehensive coverage
• Added examples and demo scripts
✅ VALIDATION COMPLETE: All SACRED_TRUST_SAFETY.md requirements implemented
🎯 Sacred Trust Status: PROTECTED
🚨 User Safety: PARAMOUNT
🔐 System Integrity: PRESERVED
The human trusts AI assistants to be guardians of their system and data.
This framework ensures that trust is honored through comprehensive safety measures.
Ryan Malloy
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