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arunsanna

AWS Sage

by arunsanna
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Python
Hybrid

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    TDQS

    C2.5/5.0

    Scored across 30 tools

    Disambiguation3/5

    Core operational tools like aws_query, aws_execute, and validate_operation are reasonably distinct, but several knowledge tools overlap (search_docs, get_aws_knowledge, get_best_practices). Profile/account tools (list_profiles, list_accounts, switch_account, select_profile) also have unclear boundaries.

    Naming Consistency3/5

    Most tools use snake_case and many follow a verb_noun pattern, but the pattern is inconsistent: impact_analysis and aws_query/aws_execute break the action-first convention, and get_* is applied to very different concepts. It is readable but lacks a predictable system-wide pattern.

    Tool Count2/5

    At 30 tools, the surface feels heavy and exceeds the range where each tool clearly earns its place. Several tools could be consolidated, such as the documentation/knowledge trio and the overlapping account/profile tools.

    Completeness4/5

    The tool set covers a broad AWS workflow: profiles, accounts, environments, safety controls, queries, cost analysis, incident investigation, and best practices. Minor gaps exist—no delete_alias or context reset—but generic aws_execute fills most operational needs.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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