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Alternatives to llm-migrate

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      Enables developers and coding agents to refactor Python codebases by re-aliasing imports and migrating dependencies, safely rewriting module paths and callsites through deterministic AST analysis instead of error-prone regex. It also surfaces dependency graphs and refactoring plans that minimize LLM token usage.
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    TDQS

    B3/5.0

    Scored across 47 tools

    Disambiguation4/5

    Most tools map to distinct workflow stages and the detailed descriptions make boundaries clear. A few near-twins remain, notably validate_research_artifact vs. validate_research_result and generate_migration_plan vs. generate_session_migration_plan, where an agent could plausibly pick the wrong one.

    Naming Consistency5/5

    All tools use imperative lower_snake_case verb_noun names with strong prefixes like get_, record_, validate_, analyze_, generate_, and submit_. Even batch/single pairs like record_change_decision(s) and submit_adaptations follow the same pattern; the minor eval/evaluation abbreviation is not enough to break consistency.

    Tool Count2/5

    47 tools is far beyond the typical well-scoped 3-15 tool surface and above the 25+ threshold. The count burdens tool selection; several near-duplicate batch/single and workspace/direct validators could be consolidated without losing capability.

    Completeness5/5

    The domain is covered end-to-end: scan, research, plan, prompt/file adaptation, change review, blockers, finalization, evaluation, regression analysis, and registry/cost helpers all exist. There are no obvious dead ends; even rare needs such as no-change files, validation disposition, and batch decisions are handled.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues