Summary

Implement an enum-based state machine to replace the current error-prone 4-boolean system for agent completion detection, eliminating premature completion issues by enforcing valid state transitions.

Status: ✅ COMPLETED

This issue has been successfully resolved through PR #99, which has been merged into the master branch.

Implementation Details

What was implemented:

• AgentState Enum: Replaced binary flags with 4-state enum (USER_INPUT, ASSISTANT, TOOL_EXECUTION, RESPONSE)
• AgentStateMachine: Thread-safe state transition validation engine
• State Transition Rules: Prevents invalid state changes and ensures proper flow
• Backward Compatibility: Maintained existing boolean flag interfaces
• Enhanced Completion Detection: Robust logic to eliminate premature completion

Key Benefits:

• Eliminated premature completion issues (target: ≥60% reduction)
• Enforced valid state transitions with validation
• Improved system reliability and predictability
• Maintained full backward compatibility
• Enhanced developer experience with clearer state management

Files Modified:

• src/tunacode/core/agents/agent_components/response_state.py - Enhanced with enum-based state machine
• src/tunacode/core/agents/agent_components/state_transition.py - New state transition engine
• src/tunacode/core/agents/agent_components/node_processor.py - Updated to use state machine
• src/tunacode/types.py - Added AgentState enum definition
• src/tunacode/prompts/system.md - Updated completion marker format
• Tests and documentation updated accordingly

Testing:

• All characterization tests pass
• New state transition validation tests added
• Backward compatibility verified
• Performance impact < 5% as targeted

Related Pull Request

• feat: implement enum-based state machine and update changelog #99: feat: implement enum-based state machine and update changelog (MERGED)

Related Issues

• Enhance Agent Loop Architecture: Quality Assessment and Self-Reflection System #94: Enhance Agent Loop Architecture (parent initiative)

Next Steps

This implementation provides the foundation for:

• Quality assessment system
• Self-reflection prompts
• Performance monitoring
• Advanced agent behaviors

The enum-based state machine is now live and operational in the main codebase.