Classify memories into semantic topics for organized retrieval.
npx skills add https://github.com/luckylhb90/bnbot --skill memory-topics
Please help me install this Agent Skill. Skill: memory-topics Source: https://github.com/luckylhb90/bnbot/tree/main/skills/memory-topics Command: npx skills add https://github.com/luckylhb90/bnbot --skill memory-topics
The memory-topics skill classifies user memories into semantic topics, enabling fast and organized retrieval without relying on keyword matching.
Use cases include organizing daily notes, improving memory-based conversations, and enabling efficient search across personal and professional memories.
Classify the memory text "I just started a new job as a software engineer" into primary topic work and secondary topic identity.
High-intent search queries and answers about installing and using this skill.
Semantic memory classification organizes memories into core topics like identity, preferences, work, and relationships to enable fast, meaningful AI retrieval without relying on keyword matching. It supports dynamic topic creation and cross-topic indexing for complex queries.
To classify a memory, assign a primary semantic topic for storage and an optional secondary topic for cross-topic indexing. For example, the memory 'I started a new job as a software engineer' maps to primary topic work and secondary topic identity.
Yes, you can create dynamic, user-specific semantic topics to organize personal and professional memories. The system scales with memory volume and supports progressive loading to optimize performance across your stored data.
The best way to organize memories for fast retrieval is semantic topic-based storage with optional secondary indexing. This approach classifies data into predefined categories like skills and context, enabling efficient search across large volumes.
Yes, the semantic memory taxonomy supports cross-topic indexing to improve recall during complex queries. By assigning secondary topics alongside primary categories, it allows the AI to retrieve interconnected memories efficiently.
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