dsh-layered-memory: DeepSeek Harness L0-L3 Layered Distillation Memory Plugin

`dsh-layered-memory` is a memory plugin designed for DeepSeek Harness, aimed at addressing issues such as context loss and repetitive questioning in long conversations and cross-session interactions. It automatically executes background processes including L0 raw conversation capture, L1 atomic memory extraction, L2 scene block integration, and L3 core profile distillation to transform conversational information into reusable memory assets. Before model execution, the plugin automatically recalls relevant memories based on length and time budgets, injecting them into the context to avoid slowing down the conversation. The plugin offers three proactive query tools, such as `memory_search`, supports four session-level memory tiers—daily, work, smart, and closed—and features a "write-only, no-read" toggle, same-session deduplication, automatic context compression resets, and time-based weighted recall functionality. The LLM token costs incurred during the distillation process are recorded.