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NeuroMedia Agent Memory

by GeniusBotsLab
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Python
Hybrid

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    TDQS

    A3.5/5.0

    Scored across 43 tools

    Disambiguation3/5

    Several tool families overlap: memory_list vs deprecated memory_list_compact, memory_list query vs memory_semantic_search vs memory_hybrid_search, and memory_create vs memory_absorb vs memory_create_batch. Descriptions are detailed enough to guide an expert agent, but an agent could still misselect among these similar read/write/search paths.

    Naming Consistency4/5

    All tools use a memory_ prefix and snake_case, making the surface highly predictable. However, the pattern is not strictly verb_noun throughout; noun-first tools like memory_stats, memory_insights, and memory_clusters are common, which is a minor deviation from the strongest convention.

    Tool Count2/5

    43 tools is too many for a coherent memory server surface, especially with maintenance, diagnostics, rate-limited rebuilds, and a deprecated alias. While the domain is broad, the count feels heavy and increases selection cost for agents.

    Completeness5/5

    The surface covers create/read/update/delete, batch operations, semantic and hybrid search, tags, documents, issues/todos/sections, linking, merging, deduplication, import/export, image migration, events, and analytics. No major lifecycle gap is apparent for an agent memory system.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

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