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libragik

universal-ai-agent-bridge

by libragik
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    TDQS

    A3.5/5.0

    Scored across 13 tools

    Disambiguation3/5

    Most tools have clear purposes, but llm_query, llm_list_models, and llm_test_connection could be confused - a user might call query when they only want to list models, or test_connection when checking availability. llm_generate_video and llm_generate_image are distinct by media type, but llm_compare, llm_council, and llm_query all involve sending prompts to multiple models, though their outputs differ significantly.

    Naming Consistency4/5

    All tools follow a consistent 'llm_' prefix with descriptive verb_noun naming (generate_video, list_models, test_connection, manage_providers). Minor inconsistency: 'llm_autodetect' is a verb alone without an object, and 'llm_cache' is a noun-only name rather than a verb_noun pair, but overall the pattern is predictable and readable.

    Tool Count5/5

    13 tools is well within the ideal range for a domain-focused server. The tools cover distinct operational areas: querying, generation, model management, caching, analytics, and multi-model orchestration, each earning its place without unnecessary duplication.

    Completeness4/5

    The surface covers core LLM operations: querying, listing models, testing connections, managing providers, generating content, comparing models, and caching. Missing operations like streaming responses, stopping/canceling ongoing requests, or batch processing are minor gaps for a local dev tool, but the main workflows are complete.

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    Resources