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Nboxff/bemula-benchmark
Nboxff/bemula-benchmark: Long-term memory has become a core component of large language model (LLM) agents. As agents accumulate personal information over long-term use, users increasingly ask them to delete sensitive or outdated facts. A memory system should honor such requests. It should remove exac...
AgentScore
10.00.00
+0.00 vs 24h ago
Adoption3.2
Quality0.0
Momentum62.5
Community8.3
Unrated pillars contribute zero
CapabilitiesCode GenerationRag
MaturityExperimental
Score breakdown
Headline plus the four pillars over time. Click any pillar below to see the signals feeding it.
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Pillar contributions
- GitHub stars5→ 13.0MCP registry listing0→ 0.0SO questions (7d)0→ 0.0
Pillar = mean of 3 scaled values = 3.2.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: PyPI monthly installs, 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
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