Implement agent memory - short-term, long-term, semantic storage, and retrieval
4.9
Rating
0
Installs
AI & LLM
Category
The skill provides a well-structured overview of agent memory systems with clear examples and architectural patterns. The description covers when to use it and the parameter schema is defined. Task knowledge includes practical code snippets for buffer, summary, and vector memory types, plus a multi-layer production architecture. Structure is excellent with concise sections, tables, and logical flow. However, novelty is limited as the examples are relatively standard LangChain patterns that a capable CLI agent could implement with moderate token usage. The skill would benefit from more implementation depth (actual working code for the ProductionMemory class, persistence backends, or complex hybrid retrieval logic) to justify being a reusable skill rather than documentation. The description could also be more specific about what the skill actually executes versus what it teaches.
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