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zahadun

by medelin
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Python
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    Deploy Server
    Context Every Agent Can ShareAgents share what they learn, hand off work, and keep it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    B3.4/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct function: peer discovery, task submission, task status retrieval, model catalog, memory search, read, write, and topic listing. There is no overlap between task and memory operations, and request/response pair (ask/task) is clearly separated.

    Naming Consistency4/5

    All tools share the 'zahadun_' prefix, and the memory tools follow a 'memory_<action>' pattern. However, some names are bare nouns (peers, task, models) while others are verbs (ask) or compound nouns (memory_topics), creating minor inconsistency in naming style.

    Tool Count5/5

    With 8 tools, the set is well-scoped for the server's purpose of managing an agent mesh network, task delegation, and shared memory. Each tool serves a clear role without redundancy or bloat.

    Completeness4/5

    Core workflows are covered: task lifecycle (submit, retrieve status/result), peer discovery, and memory operations (write, read, search, list). Minor gaps exist such as no task cancellation or listing of all tasks, but these are not essential for the primary use case.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing

    Resources