Implement working memory with long-term extraction strategy awareness

MAJOR FEATURE: Strategy-aware memory tools that understand extraction configuration

Core Components:
- WorkingMemory: Temporary storage with configurable extraction strategies
- LongTermExtractionStrategy: Abstract base for extraction logic
- MessageCountStrategy: Concrete strategy that extracts after N messages
- WorkingMemoryToolProvider: Creates tools with strategy context

Key Features:
✅ Memory tools receive extraction strategy context in descriptions
✅ Tools make intelligent decisions based on strategy configuration
✅ LLM understands when/how extraction will happen
✅ Automatic extraction based on configurable triggers
✅ Importance calculation integrated with strategy
✅ Working memory persisted in Redis with TTL
✅ Agent integration with strategy-aware tools

Memory Tools Enhanced:
- add_memories_to_working_memory: Strategy-aware memory addition
- create_memory: Decides working vs long-term based on strategy
- get_working_memory_status: Shows strategy context
- force_memory_extraction: Manual extraction trigger
- configure_extraction_strategy: Runtime strategy updates

Agent Integration:
- ClassAgent now accepts extraction_strategy parameter
- Working memory tools automatically added to agent toolkit
- System prompt includes working memory strategy context
- Messages automatically added to working memory
- Extraction happens in store_memory_node

This solves the original problem: memory tools now have full context about
the working memory's long-term extraction strategy configuration.

Author: abrookins