aiming-lab/SimpleMem: Long-term memory is essential for LLM agents that operate across multiple sessions, yet existing memory systems treat retrieval infrastructure as fixed: stored content evolves while scoring functions, fusion strategies, and answer-generation policies remain frozen at deploymen...
Pillar = mean of 1 scaled value = 19.7.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: SO questions (7d), Product Hunt upvotes, Docker Hub pulls, Crates.io downloads (90d), Tech-news mentions (30d)
Not applicable — this agent doesn't have the prerequisite (no GitHub repo, no HF mirror, etc.) for these signals to ever apply: HF downloads (30d), npm weekly installs, PyPI monthly installs, MCP registry listing
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