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chiark-ai-dev

chiark-mcp

by chiark-ai-dev
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Python
Hybrid

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    TDQS

    A3.7/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: status checking, agent discovery, score retrieval, ecosystem statistics, and outcome reporting. The descriptions make it easy to differentiate between monitoring, search, analytics, and feedback functions.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (check_agent_status, find_agent, get_agent_score, get_ecosystem_stats, report_outcome) with clear, descriptive names. The naming convention is uniform throughout the set.

    Tool Count5/5

    With 5 tools, this server is well-scoped for agent discovery and monitoring. Each tool earns its place by covering distinct aspects of the domain: discovery, evaluation, monitoring, ecosystem overview, and feedback.

    Completeness4/5

    The toolset provides strong coverage for agent discovery and quality assessment, including search, scoring, status checks, and ecosystem stats. A minor gap exists in direct agent interaction or management tools (e.g., invoking agents or configuring them), but the core workflow is well-supported.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

    Resources