long-task-continuation

To resume a long task after a session restart, you use checkpointed state to recover progress. This skill maintains checkpointed state and structured artifacts, allowing multi-step tasks to resume coherently from the last verified boundary without losing prior context.

Drift-aware progression in long-running tasks is a mechanism that validates progress against a baseline before continuing. This skill applies drift checks and evidence gating to ensure multi-step work remains coherent and verifiable before advancing to the next checkpoint.

To manage state when handing off to subagents, you establish clear boundaries and checkpointed progress. This skill provides a long-task protocol that maintains structured artifacts and verifiable evidence, ensuring seamless state handoff across different architectures.

You need evidence gating for checkpointed workflows when tasks span multiple sessions and require verifiable progress before completion. This skill enforces evidence-gated progression to ensure that each checkpoint is backed by a baseline usage record and validated artifacts.

Yes, you can use this checkpointing protocol for tasks spanning multiple architectures. The skill is explicitly designed for multi-step tasks that may restart or hand off to subagents across different architectures, maintaining coherent state through structured artifacts.

A key limitation of this evidence-gated progression is that it controls completion without executing plans or dispatching subagents itself. The skill provides drift checks and checkpointed state management, but requires external execution systems to carry out the actual task steps.