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ShadowGraph

ShadowGraph

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by LiLara-AI
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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

    A3.9/5.0

    Scored across 20 tools

    Disambiguation3/5

    The write/record tools are mostly distinct, but the read and review surface has several near-overlapping tools: search vs retrieve vs recall vs context, and review vs review_context vs reconsider vs review_signals. The descriptions explicitly cross-reference each other, which helps, but the subtle distinctions still create meaningful misselection risk.

    Naming Consistency4/5

    All tools use the same shadowgraph_ prefix and snake_case style, with mostly predictable verb_noun names. A few names are noun-only or less action-oriented, such as context and confidence_evidence, but the overall convention remains readable and consistent.

    Tool Count3/5

    Twenty tools is borderline heavy for this server, especially because several are specialized read/review variants. Each tool does appear to have a specific role in the complex memory/decision domain, but the surface feels larger than necessary.

    Completeness4/5

    The set covers the core lifecycle well: recording decisions, facts, attempts, memory, outcomes, confidence evidence, status changes, supersession, review, search, maintenance, and validation. Some referenced full-mode operations such as repair_plan and rebuild are not present, and explicit deletion/export paths are limited, but the main workflows are covered.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

    Resources