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task-checkpoint

task-checkpoint

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding sessions to save task progress, decisions, next steps, and verification evidence as local snapshots, then resume with file-change and freshness checks. It supports evidence-aware handoffs without running tests or calling model APIs.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Local-first working-state checkpoints and portable handoff packets for AI coding agents. Continuation checkpoints recover Claude Code sessions after rate limits, crashes, and compaction; packets hand tasks across tools, repos, and machines — Markdown on disk, no cloud, no telemetry.
      23
      24 npm
      4
      MIT

    TDQS

    A3.7/5.0

    Scored across 10 tools

    Disambiguation4/5

    Most tools target clearly distinct operations (init, import, export, compress, switch, restore). Minor overlap exists between tc_capture (record live changes) and tc_save (persist a step), and between tc_resume (status) and tc_show (list steps), but the two-layer model (task layer vs change layer) largely keeps them separable.

    Naming Consistency5/5

    Every tool uses the same tc_ prefix followed by a single concise verb (init, import, capture, compress, export, restore, resume, save, show, switch). The pattern is perfectly predictable throughout.

    Tool Count5/5

    Ten tools is well-scoped for a task-checkpoint lifecycle. Each tool maps to a distinct lifecycle concern (create, persist, capture, resume, inspect, restore, clean, hand off) with no filler.

    Completeness4/5

    The lifecycle is broadly covered: create, save/close, capture, status, list, switch, restore, compress, and export/import handoff. Closing a task is folded into tc_save (close=true) rather than a dedicated tool, and there is no explicit task deletion, but these are minor workable gaps.

    Maintenance

    ActivitySlowing
    ResponsivenessNo recent community issues