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papyruslabs-ai

Seshat

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    TDQS

    A4/5.0

    Scored across 27 tools

    Disambiguation4/5

    Tools have clearly distinct purposes, and descriptions actively cross-reference complementary tools (e.g., get_data_flow vs trace_data_path, query_traits vs find_by_constraint, get_dependencies vs get_blast_radius). A few pairs still require careful reading to distinguish—such as dependency tracing, blast radius, and optimal context—but the boundaries are explicitly stated.

    Naming Consistency5/5

    Every tool follows a consistent snake_case verb_noun pattern: get_, list_, find_, query_, sync_, trace_. No mixed conventions or vague names appear.

    Tool Count3/5

    27 tools is heavy for a single MCP server, though the deep code-intelligence domain justifies many specialized analyses. Several tools could likely be consolidated or grouped (e.g., multiple history and impact tools), but each addresses a distinct question.

    Completeness4/5

    Coverage is broad across structure, dependencies, data flow, history, architecture, security, testing, and dead code. Minor gaps exist for project lifecycle management (delete/update) and raw text/file search, but core analysis workflows are well covered.