avaritiachaos/dsh-plugin-memory

README excerpt

@shion-lab/dsh-plugin-memory Industrial-grade 4-tier persistent memory, self-correction, and cognitive defense engine for DeepSeek Harness ( dsh ). Featuring Git-tracked Markdown storage, dense vector semantic search, red-light pollution guards, polarity conflict detection, and half-life recency decay. Distilled from the battle-tested memory dynamics of desktop companion AI system Shion (紫苑) . 🌟 Why dsh-plugin-memory ? / 为什么需要立体持久记忆与自省防护？ By default, DeepSeek Harness operates in a stateless manner: once a session closes, all project-specific architectural rules, user preferences, and hard-earned debugging lessons are lost. Furthermore, naive memory plugins suffer from memory pollution, hallucinations, and polarity conflicts (e.g. saving stack traces or conflicting rules). @shion-lab/dsh-plugin-memory introduces a production-grade 4-tier cognitive architecture directly ported from companion agent practices (提炼自伴随式智能体「紫苑」实战记忆体系): - 🛡️ Tier 1: MemoryGuard (Red-light Anti-Pollution Gate) : - Strictly blocks stack traces ( Traceback... ), test runner output ( pytest PASSED/FAILED ), diff blocks, and API secrets ( sk-... ) from polluting memory. - ⚖️ Tier 2: MemoryConflictDetector (Sub…

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