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Engram Alpha

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Python
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    Deploy Server
    Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    B3.4/5.0

    Scored across 15 tools

    Disambiguation4/5

    Most tools have distinct targets: memory nodes, graph relations, ingestion, maintenance, and stats. A few pairs like save_memory vs extract_and_save_memory or search_memory vs auto_context could overlap, but their descriptions clarify the intended workflow. No tools are truly redundant.

    Naming Consistency4/5

    Tool names are consistently lowercase snake_case and mostly follow a verb-first pattern. The main outlier is auto_context, which is a noun phrase, and graph-related names mix save_graph_relation, query_graph, and visualize_graph. Overall the pattern remains predictable and readable.

    Tool Count5/5

    15 tools is at the upper edge of ideal but well-scoped for a memory system that combines vector storage, knowledge graph operations, ingestion, reflection, and maintenance. Each tool serves a distinct purpose, and none feel purely decorative or redundant.

    Completeness4/5

    Memory CRUD is well covered with save, search, edit, delete, and list, and graph relations have save and query support. Missing direct graph relation editing/deletion and a get-memory-by-ID tool are minor gaps, but cascade deletion and search/list provide workarounds.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources