# Technical Specification - State

**Version**: v1.0.0 | **Status**: Planned | **Last Updated**: February 2026

**Module**: `codomyrmex.orchestrator.state`  
**Last Updated**: 2026-01-29

## 1. Purpose

State machine implementations for workflow control

## 2. Architecture

### 2.1 Components

```
state/
├── __init__.py          # Module exports
├── README.md            # Documentation
├── AGENTS.md            # Agent guidelines
├── SPEC.md              # This file
├── PAI.md               # Personal AI context
└── core.py              # Core implementation
```

### 2.2 Dependencies

- Python 3.10+
- Parent module: `orchestrator`

## 3. Interfaces

### 3.1 Public API

```python
# No exports defined yet (scaffolded for future implementation)
```

### 3.2 Configuration

Environment variables:
- `CODOMYRMEX_*`: Configuration options

## 4. Implementation Notes

### 4.1 Design Decisions

1. **Immutable state transitions**: State objects are replaced on each transition rather than mutated in-place, preventing partial-update races.

### 4.2 Limitations

- State is in-memory only; no persistence across orchestrator restarts.
- Concurrent state transitions on the same workflow require external locking.

## 5. Testing

```bash
# Run tests for this module
pytest tests/orchestrator_state/
```

## 6. Future Considerations

- Distributed state sync: persist workflow state to an external store (Redis/PostgreSQL) so orchestrator restarts resume in-progress workflows without data loss.
- Checkpoint/resume: emit periodic state snapshots mid-workflow; allow agents to resume from last checkpoint rather than restarting from scratch after a failure.
- State diff and merge: provide utilities to compare two workflow state snapshots and merge non-conflicting transitions, enabling safe parallel state updates.

## Navigation

- **Self**: `SPEC.md`
- **Parent**: [../README.md](../README.md)
- **Readme**: [README.md](README.md)
- **Agents**: [AGENTS.md](AGENTS.md)
- **Repository Root**: [README.md](../../../../README.md)
